Jessica Braojos
email: jbraojos@ugr.es

Jose Benitez
email: jose.benitez@rennes-sb.com

Javier Llorens
email: fllorens@ugr.es

Laura Ruiz
email: lauraruiz@ugr.es

Jessica Braojos

Impact of IT integration on the firm's knowledge absorption and desorption

Keywords: IT integration capability, knowledge absorptive capacity, knowledge desorptive capacity, IT-enabled organizational capabilities, business value of IT

Introduction

Worldwide IT investment is projected to total $3.8 trillion in 2019, an increase of 3.2% from the expected investment of $3.7 trillion in 2018 [START_REF] Gartner | Gartner says global IT spending to grow 3.2 percent in 2019[END_REF]. A significant percentage of this worldwide investment is the firm's IT investments at the supply chain level [START_REF] Rai | Leveraging IT capabilities and competitive process capabilities for the management of interorganizational relationship portfolios[END_REF].

As the global competition among firms has been focused at the supply chain level (instead of the focal firm), the firm's integration of IT systems with other organizations (IT integration) has become a critical IT capability to create business value [START_REF] Rai | Firm performance impacts of digitally enabled supply chain integration capabilities[END_REF]. The construct IT integration has been examined in IS research in the different contexts: mergers and acquisitions (Benitez et al. 2018a), supply chain [START_REF] Ward | Impact of information technology integration and lean/just-in-time[END_REF]Zhou 2006, Lai et al. 2008), and IT outsourcing [START_REF] Ceci | Impact of IT offerings strategies and IT integration capability on IT vendor value creation[END_REF]. We focus on IT integration capability in the supply chain1 , which is conceptualized as the firm's ability to integrate IT systems of the firm and IT systems of other organizations to coordinate activities with external agents (e.g., suppliers, customers, public institutions, competitors, etc.) (Bharadwaj et al. 2007, Rai and[START_REF] Rai | Leveraging IT capabilities and competitive process capabilities for the management of interorganizational relationship portfolios[END_REF].

Currently, firms across industries are increasingly opening up their innovation processes by exchanging their knowledge with external agents [START_REF] Chesbrough | Open business models: How to thrive in the new innovation landscape[END_REF][START_REF] French | Toward a holistic understanding of continued use of social networking tourism: A mixed-methods approach[END_REF][START_REF] Roldan | Examining desorptive capacity in supply chains: The role of organizational ambidexterity[END_REF]. A firm that consistently creates and sustains close relationships with suppliers or customers is in a better position to identify and assimilate new external knowledge (e.g., technological advancements, regulation changes, and customers' preferences) and therefore be able to use this knowledge to increase firm performance (Kostopoulos et al. 2011, Setia and[START_REF] Setia | How information systems help create OM capabilities: Consequences and antecedents of operational absorptive capacity[END_REF].

Consequently, firms require certain organizational capabilities like abilities to manage internal and external knowledge (knowledge management) to respond effectively to the market [START_REF] Tanriverdi | Information technology relatedness, knowledge management capability, and performance of multibusiness firms[END_REF][START_REF] Malone | The big idea: the age of hyperspecialization[END_REF]. In this sense, the organizational capabilities associated to knowledge management remain critical for firms to be able to compete in the era of digital disruption and supply chain management-based competition (Grant 1996, Lichtenthaler and[START_REF] Lichtenthaler | A capability-based framework for open innovation: Complementing absorptive capacity[END_REF].

How does the firm's IT integration capability affect knowledge management capabilities to create business value? This is the general research question this study aims to examine and answer.

We distinguish and focus on two critical knowledge management capabilities: knowledge absorptive capacity [START_REF] Cohen | Absorptive capacity: A new perspective on learning and innovation[END_REF] and knowledge desorptive capacity [START_REF] Lichtenthaler | A capability-based framework for open innovation: Complementing absorptive capacity[END_REF]. Knowledge absorptive capacity refers to the firm's ability to acquire, assimilate, transform, and exploit external core/primary knowledge for commercial ends [START_REF] Cohen | Statistical power analysis for Behavioral Sciences[END_REF]Levinthal 1990, Zahra andGeorge 2002). Knowledge desorptive capacity refers to the firm's ability to identify and transfer superficial/secondary (i.e., less important) knowledge2 to external partners (e.g., suppliers, customers, public institutions, competitors, etc.) (Lichtenthaler and[START_REF] Lichtenthaler | A capability-based framework for open innovation: Complementing absorptive capacity[END_REF][START_REF] Lichtenthaler | Technology transfer across organizational boundaries: Absorptive capacity and desorptive capacity[END_REF]. Companies may not be interested in desorbing core knowledge that can hamper their future strategic positions, but may be interested in desorbing superficial/secondary knowledge while protecting their primary knowledge to obtain incomes, developing partnerships, or entering new markets. While knowledge absorptive capacity covers the outside-inside primary knowledge transfer process, knowledge desorptive capacity refers to an inside-outside secondary knowledge transfer process [START_REF] Mortara | How do large multinational companies implement open innovation?[END_REF]Minshall 2011, Hu et al. 2015). In this sense, this study covers the key knowledge transfer activities of the continuum for the focal firm and its supply chain. How does the firm's IT integration capability affect the firm's knowledge absorption and desorption? This is the idiosyncratic and specific research question this study aims to examine and answer.

Prior IS research has focused on studying the impact of IT on knowledge absorption [START_REF] Roberts | Absorptive capacity and Information Systems research: Review, synthesis, and directions for future research[END_REF]. This body of research has been studied from a wide range of theoretical approaches such as knowledge management [START_REF] Alavi | Knowledge management and knowledge management systems: Conceptual foundations and research issues[END_REF]Leidner 2001, Felipe et al. 2016), IT governance [START_REF] Limaj | The impact of social information system governance, utilization, and capabilities on absorptive capacity and innovation: A case of Austrian SMEs[END_REF], IT innovation [START_REF] Joshi | Changing the competitive landscape: Continuous innovation through IT-enabled knowledge capabilities[END_REF][START_REF] Carlo | A knowledge-based model of radical innovation in small software firms[END_REF], and business value of IT [START_REF] Bhatt | Types of information technology capabilities and their role in competitive advantage: An empirical study[END_REF]. [START_REF] Liu | The impact of IT capabilities on firm performance: The mediating roles of absorptive capacity and supply chain agility[END_REF] examined the effect of IT capabilities on firm performance through absorptive capacity. [START_REF] Joshi | Changing the competitive landscape: Continuous innovation through IT-enabled knowledge capabilities[END_REF] considered absorptive capacity as an IT-enabled knowledge capability and examine how it was able to increase innovation outputs. [START_REF] Limaj | The impact of social information system governance, utilization, and capabilities on absorptive capacity and innovation: A case of Austrian SMEs[END_REF] argue that social information systems act as antecedents of absorptive capacity and that the combination of both enables the firm to generate innovation outcomes. Therefore, prior IS research has argued the impact of IT investments on the development of knowledge absorptive capacity to achieve business goals. However, although prior IS research has not examined whether IT integration may influence the development of knowledge absorptive capacity, we believe it is a critical aspect to shed light given the new rules of the business landscape: the supply chain-based competition/coopetition. Similarly, prior IS research has not paid enough attention to the role of IT (neither IT integration) in the knowledge desorption, although IT integration might become a foundational capability to create and appropriate business value. Firms can be interested in transferring secondary knowledge (e.g., soft technology) to other external organizations to obtain a licensing income, entry into a foreign market, or access to core knowledge from these external partners (Lichtenthaler andLichtenthaler 2010, Roldan et al. 2018).

In the current business landscape, firms cannot operate isolated, but depend on external resources and partners [START_REF] Rai | Leveraging IT capabilities and competitive process capabilities for the management of interorganizational relationship portfolios[END_REF]. However, alliances are not always easy to manage because many of them face strong difficulties in benefiting from the management of knowledge, having doubts about the effectiveness of knowledge exchange, and therefore, becoming reluctant to involve in these processes [START_REF] Kostopoulos | Absorptive capacity, innovation, and financial performance[END_REF]. The failure in managing knowledge can lead to disastrous outcomes ultimately hampering the competitive position of the firm. Given the huge investment firms are making on IT, this is a good opportunity to show whether leveraging a critical IT capability such as IT integration matters in the management of knowledge and may be key to the successful building of capitalization of knowledge. Integrated IT systems offer technical platforms and capabilities to build knowledge management capabilities. This has become critical as competition is now at the inter-organizational (instead of firm) level through the supply chain and alliances with others companies.

We introduce conceptually the construct of knowledge desorptive capacity to IS research and examine the impact of IT integration capability on the firm's knowledge absorption and desorption.

Our central proposition is that the firm's ability to integrate IT systems of the firm and IT systems of external partners (IT integration capability) enables the focal firm to coordinate their business activities with external partners in a better way, which in turn facilitates to absorb core knowledge and transfer superficial knowledge with external partners to increase its business benefits.

We ran an empirical study in Spain to test our proposed theory. We find that IT integration capability enables the firm to absorb and desorb knowledge with other organizations, which in turn improves firm performance. In this sense, the empirical analysis supports our theory. Figure 1 shows the proposed research model. This research provides two key contributions to the IS research: 1) We introduce the concept of knowledge desorptive capacity in the IS research and provide a scale for its measure, 2) we provide and test a theory of IT integration impact on the firm's knowledge absorption and desorption.

The paper continues as follows: 1) the next section presents the theoretical framework, the conceptualization of key constructs, and hypotheses development, 2) the third section explains the research design, 3) the fourth section exposes the empirical analysis and results, 4) the fifth section incorporates the discussion and conclusions.

Theory, the conceptualization of key constructs, and hypotheses development

IT-enabled organizational capabilities perspective

Business value of IT is one of the golden lines of IS research that captures much attention from IS scholars. Grounded in the resource-based theory and the organizational capabilities theory, the socalled IT-enabled organizational capabilities have emerged as the dominant and well-established perspective to explain how the firm's IT resource investments influence firm performance. ITenabled organizational capabilities perspective has been proven to be one of the strongest and more evidenced bodies of IS research to disentangle the IT productivity paradox. This perspective suggests that IT resources and capabilities influence firm performance through the development of business/organizational capabilities, thus emphasizing the enabling role of IT (the mediation hypothesis) in creating business value [START_REF] Benitez | Information technology, the organizational capability of proactive corporate environmental strategy and firm performance: A resource-based analysis[END_REF]. Prior IS research consistent with this perspective has found that organizational learning, knowledge management (Tanriverdi 2005, Pavlou and[START_REF] Pavlou | From IT leveraging competence to competitive advantage in turbulent environments: The case of new product development[END_REF], corporate entrepreneurship [START_REF] Chen | IT capabilities and product innovation performance: The roles of corporate entrepreneurship and competitive intensity[END_REF], and business flexibility [START_REF] Chen | Improving strategic flexibility with information technologies: Insights for firm performance in an emerging economy[END_REF], Benitez et al. 2018a[START_REF] Benitez | How information technology influences opportunity exploration and exploitation firm's capabilities[END_REF]) are intermediate processes/organizational capabilities through which IT influences firm performance. We draw on this perspective to propose an indirect impact of IT integration capability on firm performance through knowledge absorptive and knowledge desorptive capacities.

The organizational capabilities theory suggests that variance in performance comes from three types of organizational capabilities: dynamic capability, operational capability, and dual-purpose capability [START_REF] Helfat | Untangling dynamic and operational capabilities: Strategy for the (n)ever-changing world[END_REF]Winter 2011, Benitez et al. 2018a). Dynamic capabilities refer to the ability of the firm to build, integrate, and reconfigure internal and external resources/capabilities, and developing new ones to respond to changes in the environment [START_REF] Teece | Explicating dynamic capabilities: The nature and microfoundations of (sustainable) enterprise performance[END_REF]. Operational capabilities refer to the ability of the firm to execute operational routines required to perform operational activities (Wu et al. 2010, Benitez et al. 2018c). Dual-purpose capabilities refer to organizational capabilities that can be used at corporate and operational level, then being dynamic as well as operational [START_REF] Helfat | Untangling dynamic and operational capabilities: Strategy for the (n)ever-changing world[END_REF]Winter 2011, Benitez et al. 2018a). Knowledge absorptive capacity and knowledge desorptive capacity have been extensively proposed in prior literature as dynamic capabilities that assist in managing knowledge (Zahra and George 2002[START_REF] Malhotra | Absorptive capacity configurations in supply chains: gearing for partner-enabled market knowledge creation[END_REF][START_REF] Lichtenthaler | The drivers of technology licensing: An industry comparison[END_REF]). In this sense, we use organizational capabilities theory to conceptualize knowledge absorptive and knowledge desorptive capacities and to explain their causal influence on firm performance.

Conceptualization of key constructs

The key concepts examined in this study are IT integration capability, knowledge absorptive capacity, knowledge desorptive capacity, and firm performance. IT integration capability is the firm's ability to integrate its IT systems and the IT systems of external partners (e.g., suppliers, customers, public institutions, competitors, etc.) to coordinate business activities with the external partners and provide consistent access to relevant information [START_REF] Bharadwaj | The performance effects of complementarities between information systems, marketing, manufacturing, and supply chain processes[END_REF][START_REF] Rai | Leveraging IT capabilities and competitive process capabilities for the management of interorganizational relationship portfolios[END_REF][START_REF] Setia | How information systems help create OM capabilities: Consequences and antecedents of operational absorptive capacity[END_REF]. IT integration provides an integrated and consistent access and sharing to order, production, customer (e.g., service contracts, feedback) and market-related data [START_REF] Bharadwaj | The performance effects of complementarities between information systems, marketing, manufacturing, and supply chain processes[END_REF][START_REF] Chong | Can e-business adoption be influenced by knowledge management? An empirical analysis of Malaysian SMEs[END_REF].

Knowledge absorptive capacity refers to the firm's ability to acquire, assimilate, transform, and exploit external core knowledge for commercial ends [START_REF] Cohen | Absorptive capacity: A new perspective on learning and innovation[END_REF]. Knowledge absorptive capacity is composed of four ingredients: knowledge acquisition, knowledge assimilation, knowledge transformation, and knowledge exploitation. Knowledge acquisition refers to the firm's ability to gather and identify internal (i.e., within the firm) or external (e.g., market) knowledge about process, product, logistics, and distribution related to innovation. It also involves the development of new knowledge or insights that have the potential to influence the development of new products [START_REF] Setia | How information systems help create OM capabilities: Consequences and antecedents of operational absorptive capacity[END_REF]. Knowledge assimilation refers to the analysis, interpretation, and understanding of the information and knowledge obtained. Knowledge transformation refers to the transformation of existing information into new knowledge and to the integration of the new information and knowledge acquired with the existing knowledge of the firm. Finally, knowledge exploitation refers to the ability of exploiting the new integrated information and knowledge into concrete applications or products while constantly considering better ways to exploit knowledge (Zahra and George 2002). Zahra and George (2002) recognized absorptive capacity as a dynamic capability categorized into two main subsets: potential and realized. Potential absorptive capacity enables a firm's receptiveness to external knowledge (i.e., acquire and assimilate knowledge), while realized absorptive capacity reflects a firm's capacity to leverage absorbed knowledge and transform it into innovation outcomes (i.e., transform and exploit knowledge). Potential absorptive capacity is conceptually covered in our study through knowledge acquisition and knowledge assimilation.

Realized absorptive capacity is captured in our investigation through knowledge transformation and knowledge exploitation. We conceptualized and operationalized absorptive capacity as second-order construct composed of four dimensions (knowledge acquisition, knowledge assimilation, knowledge transformation, and knowledge exploitation). This choice was preferred to operationalize knowledge absorptive capacity as two second-order constructs (potential and realized absorptive capacities) as we believe it is theoretically clear, statistically more parsimonious, and consistent with prior research. 3 Knowledge desorptive capacity refers to the firm's ability to identify and transfer superficial knowledge to external partners (e.g., suppliers, customers, public institutions, competitors, etc.) (Lichtenthaler and[START_REF] Lichtenthaler | A capability-based framework for open innovation: Complementing absorptive capacity[END_REF][START_REF] Lichtenthaler | Technology transfer across organizational boundaries: Absorptive capacity and desorptive capacity[END_REF]. We argue that desorptive capacity has two main components: knowledge identification and knowledge transfer.

Knowledge identification refers to the firm's ability to identify external knowledge opportunities that could be relevant to suppliers, customers, or other external organizations (e.g., public institutions and competitors). Knowledge transfer involves the transfer of superficial knowledge (e.g., consultations on product design ideas, production processes, and routines for efficiency, schedule, or technical problems) to external agents [START_REF] Dyer | Relation-specific capabilities and barriers to knowledge transfers: Creating advantage through network relationships[END_REF][START_REF] Lichtenthaler | A capability-based framework for open innovation: Complementing absorptive capacity[END_REF][START_REF] Potter | Help or hindrance? Causal ambiguity and supplier involvement in new product development teams[END_REF].

The process of desorbing constitutes the opposite direction of absorbing (Lichtenthaler andLichtenthaler 2009, Lichtenthaler 2013). That is, knowledge desorptive capacity refers to an insideoutside secondary knowledge transfer process [START_REF] Mortara | How do large multinational companies implement open innovation?[END_REF]Minshall 2011, Hu et al. 2015). There are some contradictory interests when transferring knowledge. On one hand, core knowledge is understood as a source of power and competitive advantage and therefore, firms may be reluctant to share (core) knowledge that has a strategic value for their position in the market [START_REF] Chiambaretto | All for one and one for all?": Knowledge broker roles in managing tensions of internal coopetition: The Ubisoft case[END_REF]. On the other hand, firms can have some benefits and strategic interests when transferring superficial knowledge (i.e., reducing costs, sharing risks, obtaining licensing incomes, entering into a foreign market, or exploiting innovative solutions from combining knowledge) [START_REF] Lichtenthaler | Technology transfer across organizational boundaries: Absorptive capacity and desorptive capacity[END_REF]. In this sense, organizations can protect from spilling over strategic/core knowledge and can prevent imitation by transferring superficial knowledge. First, organizations can deliver knowledge with a delay that allows the firm to maintain the first-mover 3 We repeated the empirical analysis by operationalizing knowledge absorptive capacity as two second-order constructs (potential and realized absorptive capacities) where potential absorptive capacity leads to realized absorptive capacity but every other relationship is kept the same as in the proposed research model. We obtain very similar results (β Potential absorptive capacity → Realized absorptive capacity = 0.692 *** ), which suggests the operationalization of knowledge absorptive capacity does not affect the results, findings, and contributions of this study.

advantage [START_REF] Chiambaretto | All for one and one for all?": Knowledge broker roles in managing tensions of internal coopetition: The Ubisoft case[END_REF]. Second, organizations can use causal ambiguity by transferring complex or noncodified knowledge that makes it difficult to understand the causes and effects [START_REF] Dyer | Relation-specific capabilities and barriers to knowledge transfers: Creating advantage through network relationships[END_REF]Hatch 2006, Potter and[START_REF] Potter | Help or hindrance? Causal ambiguity and supplier involvement in new product development teams[END_REF]. Third, organizations can share redundant or supplementary knowledge that overlaps with the receiver's knowledge [START_REF] Knudsen | The relative importance of interfirm relationships and knowledge transfer for new product development success[END_REF].

Although value creation has been typically related to cooperation, and value appropriation to competition, firms may be involved in the so-called coopetition phenomenon. Aggressive and disruptive companies [START_REF] References Ajamieh | IT infrastructure and competitive aggressiveness in explaining and predicting performance[END_REF]) play often the game of coopetition to finally compete, that is, they cooperate with external competing organizations (e.g., competitors) to capture core knowledge but only giving superficial knowledge [START_REF] Hoffmann | The interplay of competition and cooperation[END_REF] and then "attacking" in the market. This is what we call opportunistic behavior, a key assumption of our study. Companies play to say that they cooperate to at the end compete and attack. World-class companies have begun to desorb knowledge as a part of their corporate strategies. For example, based on a strong knowledge desorptive capacity with its suppliers' network, Toyota improved their productivity and quality from transferring production knowledge. Because of this transferring of knowledge, Toyota's suppliers were able to learn how to manufacture better products for Toyota. However, this suppliers' learning was only suitable to Toyota's routines and policies, making it difficult to spill over knowledge to benefit Toyota's competitors. As a result, Toyota's vehicles had 40% fewer defects than their competitors with the same supplier network [START_REF] Dyer | Relation-specific capabilities and barriers to knowledge transfers: Creating advantage through network relationships[END_REF]. Finally, we focus on overall firm performance in terms of innovation, marketing, and financial facets [START_REF] Pavlou | From IT leveraging competence to competitive advantage in turbulent environments: The case of new product development[END_REF]El Sawy 2006, Braojos et al. 2019). Table 1 presents the definition, dimensions, and informing source of our key constructs.

IT integration capability and knowledge absorptive capacity

IT integration capability may affect knowledge absorptive capacity. The integration of IT systems of the focal firm and the IT systems of its external partners help the focal firm to acquire, assimilate, transform, and exploit core knowledge from them. First, IT integration enables a firm to exchange rich information in real time (e.g., changes in plans for production and new trip schedule) and consequently facilitates the process of knowledge acquisition (Rai andTang 2010, Ngai et al. 2012). For example, Cisco created an e-hub connecting suppliers and the company through Internet, allowing all firms to have the same demand and supply data to respond quickly to demand changes [START_REF] Lee | The triple-A supply chain[END_REF]. Second, integrated IT platforms span the organization boundaries connecting experts across organizations. When experts across organizations have access to and share uniform knowledge, interpretation, and analysis of this knowledge are likely to converge, then assimilation becomes easier [START_REF] Setia | How information systems help create OM capabilities: Consequences and antecedents of operational absorptive capacity[END_REF]Patel 2013, Liu et al. 2016). Third, IT integration enables coordination and discussion among external agents, becoming easier for firms to compare and integrate new and existing knowledge [START_REF] Setia | How information systems help create OM capabilities: Consequences and antecedents of operational absorptive capacity[END_REF]. For instance, an integrated IT platform that supports electronic meetings makes the discussion of new market trends and the interpretation of existing knowledge in a different manner more likely to occur [START_REF] Bharadwaj | The performance effects of complementarities between information systems, marketing, manufacturing, and supply chain processes[END_REF]. Last, integrated IT platforms facilitate not only information flow across departments, but also information transparency, which allows a consistent view of the information and facilitates the refinement of existing and new core knowledge to exploit it. Integrated cross-boundary technologies such as ecommerce or social media technology leads to exchange relationships building across the firm and the external partners, allowing the firm to consider new ways of exploiting knowledge and competitive information [START_REF] Li | Digital transformation by SME entrepreneurs: A capability perspective[END_REF][START_REF] Song | Impact of the usage of social media in the workplace on team and employee performance[END_REF]. In sum, IT integration capability enables knowledge exchange with internal and external agents, enhancing knowledge acquisition, assimilation, transformation, and the exploitation of core knowledge. Therefore, we hypothesize that:

H1: There is a positive relationship between IT integration capability and knowledge absorptive capacity.

Table 1: Definition of key constructs

IT integration and knowledge desorptive capacity

We propose that IT integration capability may enable the firm to develop a knowledge desorptive capacity. IT integration capability facilitates communication and information sharing along the supply chain of the firm while spanning organizational boundaries, providing access to external agents' information and data, and improving the visibility of this information [START_REF] Lichtenthaler | The drivers of technology licensing: An industry comparison[END_REF][START_REF] Liu | The impact of IT capabilities on firm performance: The mediating roles of absorptive capacity and supply chain agility[END_REF], which in turn may enable the focal firm to identify opportunities inside and outside its market to desorb superficial knowledge to external partners. Thus, we expect that the integration of the IT systems of the focal firm with the IT systems of its partners, enable the focal firm to identify knowledge desorption opportunities. On the other side, IT integration capability may enable the focal company to transfer superficial knowledge. Integrated IT systems are likely to become a common digital platform shared by the focal firm and its supply chain, allowing the firm to transfer superficial knowledge about nonrelevant products, suppliers, customers, markets, or technology [START_REF] Pinjani | Trust and knowledge sharing in diverse global virtual teams[END_REF]. Therefore, if the firm is able to have better and more integrated IT systems with its partners, this will enable the transfer/desorption of knowledge [START_REF] Bharadwaj | The performance effects of complementarities between information systems, marketing, manufacturing, and supply chain processes[END_REF]. In summary, IT integration capability enables an organization to identify opportunities to desorb knowledge and transfer internal secondary knowledge to an external partner. Therefore, we hypothesize that:

H2: There is a positive relationship between IT integration capability and knowledge desorptive capacity.

Knowledge absorptive capacity and knowledge desorptive capacity

This study proposes that the firm's knowledge absorptive capacity is positively related to the firm's knowledge desorptive capacity. First, prior IS research on organizational ambidexterity has found an activity sequence between knowledge/business opportunities exploration and knowledge/business opportunities exploitation [START_REF] Benitez | How information technology influences opportunity exploration and exploitation firm's capabilities[END_REF][START_REF] Benitez | IT-enabled knowledge ambidexterity and innovation performance in small U.S. firms: The moderator role of social media capability[END_REF] in a way that exploration precedes exploitation. Drawn on this prior IS research, we argue that knowledge absorptive capacity may be an antecedent of knowledge desorptive capacity. 4 Second, firms exhibit an opportunistic behavior and it is rational to expect they focus more on knowledge absorption than on knowledge desorption. Thus, a firm may be interested in identifying knowledge transfer opportunities and transferring superficial knowledge to external partners (knowledge desorptive capacity) once has guaranteed the sufficient level of core knowledge internally to survive and compete in the market [START_REF] Lichtenthaler | A capability-based framework for open innovation: Complementing absorptive capacity[END_REF], and ensuring the company is special for customers. [START_REF] Hu | Outbound open innovation in biopharmaceutical out-licensing[END_REF] found that the number of in-licensing deals with external partners leads to a higher number of out-licensing deals. For example, the Fiat Research Centre (CRF), in a period of recession, decided to take an open innovation perspective. It was achieved, first, through the influx of resources from outside the Fiat Group to jointly develop know-how, and secondly, transferring technologies to industries other than the automotive. The revenues from the transfer of CRF technologies to external customers and cash flows resulting from CRF's participation in public-funded research projects allowed CRF to continue investing in the area of fuel-efficient engine technologies [START_REF] Di Minin | Fiat: Open innovation in a downturn (1993-2003)[END_REF]. This example illustrates that in some companies knowledge absorption can be an antecedent (and can be associated) with a subsequent knowledge desorption. Therefore, we hypothesize that:

H3: There is a positive relationship between knowledge absorptive capacity and knowledge desorptive capacity.

Knowledge absorptive capacity and firm performance

This study proposes a positive relationship between knowledge absorptive capacity and firm performance based on the following arguments. First, firms with the ability to acquire and assimilate new core knowledge such as know-how, customer knowledge, core technologies, operational or market knowledge can rapidly detect new business opportunities [START_REF] Benitez | How information technology influences opportunity exploration and exploitation firm's capabilities[END_REF]. This capability helps firms to envision and identify customer preferences and new tendencies more easily, being easier to understand the market, and pioneering in the development of new products/services, hence improving firm performance [START_REF] Engelen | Entrepreneurial orientation in turbulent environments: The moderating role of absorptive capacity[END_REF][START_REF] Leal | From potential absorptive capacity to innovation outcomes in project teams: The conditional mediating role of the realized absorptive capacity in a relational learning context[END_REF].

For example, Air Products and Chemicals (a global corporation that sells gases and chemical products for industrial purposes) uses strategies like external partnering or Internet-based knowledge providers to identify external ideas that make the innovation process to work faster [START_REF] Gronlund | Open innovation and the stage-gate process: A revised model for new product development[END_REF]. Second, firms with the ability to transform and exploit new knowledge are more likely to respond to changes and effectively shape their internal processes to exploit new opportunities (Liu et al. 2013, Setia and[START_REF] Setia | How information systems help create OM capabilities: Consequences and antecedents of operational absorptive capacity[END_REF]. Firms with the ability to integrate new and existing knowledge may easily respond to changes and generate innovation outcomes [START_REF] Leal | From potential absorptive capacity to innovation outcomes in project teams: The conditional mediating role of the realized absorptive capacity in a relational learning context[END_REF]. For example, to make snacks more novel and fun, Procter & Gamble came up with the idea of printing pop culture images on Pringles. To do so, they used their absorptive capacity to find and exploit an ink-jet method developed by a small bakery in Italy for printing edible images, leading to an important sales growth [START_REF] Huston | Connect and develop: Inside Procter & Gamble's new model for innovation[END_REF]. In conclusion, the ability to monitor, assimilate, and leverage external core knowledge provide firms up-to-date critical knowledge on customers and markets, which will improve innovation, marketing, and financial firm performance (Zahra and George 2002). Then, firms with superior knowledge absorptive capacity are more likely to exhibit higher firm performance [START_REF] Pavlou | From IT leveraging competence to competitive advantage in turbulent environments: The case of new product development[END_REF]El Sawy 2006, Benitez et al. 2018d). Therefore, we hypothesize that:

H4: There is a positive relationship between knowledge absorptive capacity and firm performance.

Knowledge desorptive capacity and firm performance

This study proposes that a positive relationship exists between knowledge desorptive capacity and firm performance. Firms may have different motivations to desorb superficial knowledge with the final-end to increase firm performance. First, firms may transfer superficial knowledge to external organizations established in different product markets to access these new/foreign markets to compete and increase market share, revenues, and profitability, thus improving firm performance [START_REF] Lichtenthaler | Technology transfer across organizational boundaries: Absorptive capacity and desorptive capacity[END_REF]. For example, in the case of technology transfer, firms usually avoid transferring technology to firms within the same industry because of the existence of competitive threats, but instead, they prefer distant markets. This setting constitutes the first motivation to desorb superficial knowledge and improve firm performance: desorbing knowledge in a foreign market to make an entry into this market.

Second, another motivation for firms to identify knowledge transfer opportunities and transferring knowledge to external partners is to have access to the core knowledge from the external partner and thus increase firm performance. For example, in the bio-pharmaceutical industry the out-licensing is of particular importance to have access to the intellectual property of partners such as university know-how that may enhance the research productivity of private firms, and therefore its firm performance [START_REF] Hu | Outbound open innovation in biopharmaceutical out-licensing[END_REF]. This is the second mechanism through which knowledge desorptive capacity may influence firm performance. Finally, firms can also desorb knowledge to obtain a licensing income and generate business benefits. In summary, knowledge desorptive capacity can improve performance when firms are able to identify opportunities to exploit its superficial knowledge to obtain monetary gains (e.g., licensing) and strategic or noneconomic gains (e.g., having access to more critical knowledge or establishing in new markets) [START_REF] Roldan | Examining desorptive capacity in supply chains: The role of organizational ambidexterity[END_REF]. Therefore, we hypothesize that:

H5: There is a positive relationship between knowledge desorptive capacity and firm performance.

Research design and execution

Sample and data

Because the measures for the constructs studied in this research are not available directly in archival data, we decided to run a survey. The survey instrument was developed following the guidelines provided in prior research [START_REF] Pavlou | From IT leveraging competence to competitive advantage in turbulent environments: The case of new product development[END_REF]El Sawy 2006, Benitez et al. 2018a). We started the data collection by using the list of the 5000 most admired large firms in Spain included in the Actualidad Economica database in 2015 (http://www.actualidadeconomica.com/). Actualidad Economica is a Spanish business magazine that annually publishes a ranking with the most admired firms in Spain based on sales and other business variables (e.g., innovation activity and employer brand value) [START_REF] Benitez | Information technology, the organizational capability of proactive corporate environmental strategy and firm performance: A resource-based analysis[END_REF], Benitez et al. 2018a[START_REF] Benitez | How information technology influences opportunity exploration and exploitation firm's capabilities[END_REF], 2020a). We selected the Spanish market for the following reasons: 1) Spain represents one of the top five economies of the European Union in terms of the gross domestic product, 2) Spain is an important worldwide market for IT investments, with a forecast of total IT investments of 41,600 million Euros in 2018 (IDC Spain, 2017), and 3) digitization of the supply chain is one of the priorities of Spanish companies [START_REF] Patwardhan | The digital supply chain's missing link: Focus[END_REF]).

This is one of the two studies of a broader research project that aims to examine the impact of technology (IT systems and social media) on a critical portfolio of organizational capabilities and firm performance. Prior to the survey administration, we selected a group of industries that is highly active in new product development [START_REF] Pavlou | From IT leveraging competence to competitive advantage in turbulent environments: The case of new product development[END_REF]

Measures

Constructs can be operationalized as emergent variables (i.e., composite model) or latent variables (i.e., factor model) [START_REF] Benitez | How to perform and report an impactful analysis using partial least squares: Guidelines for confirmatory and explanatory IS research[END_REF]). Latent variables are variables that are not directly observed but inferred through a measurement model from other variables that are observed (directly measured) [START_REF] Borsboom | The theoretical status of latent variables[END_REF]. These types of variables can be operationalized as reflective and causal-formative (Henseler 2017a). Latent variables are usually used in behavioral research to operationalized concepts such as attitudes or personality traits [START_REF] Henseler | Is the whole more than the sum of its parts? On the interplay of Marketing and Design research[END_REF]. The causalformative measurement model changes the direction of causality between the indicators and the construct. In this type of measurement model, contrary to the reflective measurement model, indicators cause the latent variable. On the other hand, composite modeling is the usual way to model artifacts. Composites are applied to model abstractions of artifacts as a combination of ingredients where the indicators make up the construct (they do not cause the artifact) [START_REF] Henseler | Is the whole more than the sum of its parts? On the interplay of Marketing and Design research[END_REF], 2017a[START_REF] Benitez | How to perform and report an impactful analysis using partial least squares: Guidelines for confirmatory and explanatory IS research[END_REF]. Artifacts are usually objects that are created by managers, staff or firm, representing emergent, strong, complex, and "firm-made" concepts (Benitez et al. 2018a[START_REF] Benitez | IT-enabled knowledge ambidexterity and innovation performance in small U.S. firms: The moderator role of social media capability[END_REF][START_REF] Benitez | How to perform and report an impactful analysis using partial least squares: Guidelines for confirmatory and explanatory IS research[END_REF]. Based on these distinctions, we conceptualized and operationalized all the constructs included in the research model as emergent variables, thus generating a composite model.

IT integration capability:

IT integration capability was measured as a composite first-order construct composed of five items by adapting the scale from [START_REF] Setia | How information systems help create OM capabilities: Consequences and antecedents of operational absorptive capacity[END_REF]. This scale evaluates in a five-point Likert scale the extent to which the firm's integration of IT systems facilitates integrated access and sharing of data with external partners. evaluates in a four-item scale the firm's ability to combine new and existing knowledge (Liu et al. 2013, Setia and[START_REF] Setia | How information systems help create OM capabilities: Consequences and antecedents of operational absorptive capacity[END_REF]. Knowledge exploitation measures in a four-item scale the firm's ability to use external knowledge to achieve business' goals (Liu et al. 2013, Setia and[START_REF] Setia | How information systems help create OM capabilities: Consequences and antecedents of operational absorptive capacity[END_REF]. The four dimensions of knowledge absorptive capacity are specified as composite at first-order level.

Knowledge absorptive capacity:

Knowledge desorptive capacity:

Knowledge desorptive capacity is a new developed scale that measures the firm's ability to identify and transfer superficial knowledge to external partners (e.g., suppliers, customers, public institutions, competitors, etc.) (Lichtenthaler and[START_REF] Lichtenthaler | A capability-based framework for open innovation: Complementing absorptive capacity[END_REF][START_REF] Lichtenthaler | Technology transfer across organizational boundaries: Absorptive capacity and desorptive capacity[END_REF]. We generated the items based on prior theoretical literature (Lichtenthaler andLichtenthaler 2009, 2010) that proposes desorptive capacity as composed by two key ingredients (i.e., identification and transfer of knowledge). The measurement was driven by theory and some cautions were taken into consideration to ensure content validity.

We reviewed the seminal theoretical desorptive capacity literature to generate an initial pool of items. All items were measured on a scale from 1 to 5 (1: Strongly disagree, 5: Strongly agree).

The list of items was sent to four scholars to verify whether they measured what they were supposed to measure. Valuable comments were used to refine the list of items and a pretest with seven IT/business executives was performed to ensure validity and reliability. As a result, we conceptualize the construct of knowledge desorptive capacity as a second-order composite construct composed by two first-order constructs: knowledge identification (three items) and knowledge transfer (five items). Knowledge identification measures the firm's ability to recognize and gather external knowledge that could be of interest for external organizations (e.g., suppliers, customers, public institutions, competitors), while knowledge transfer measures the firm's ability to transfer superficial knowledge to external agents. The two dimensions were specified as composite at first-order level.

Firm performance:

Firm performance was measured with five items in terms of innovation, marketing, and financial facets in the last two years by adapting the scales of [START_REF] Pavlou | From IT leveraging competence to competitive advantage in turbulent environments: The case of new product development[END_REF] and Kim and Atuahene-Gima (2010).

Control variables on firm performance:

Differences in firm performance can be attributed to differences in the portfolio of resources possessed by the firm, firm age, industry, total IT investment [START_REF] Benitez | Information technology, the organizational capability of proactive corporate environmental strategy and firm performance: A resource-based analysis[END_REF], investment in innovation activities, and the implementation of quality management programs [START_REF] Benitez | How information technology influences opportunity exploration and exploitation firm's capabilities[END_REF]). We thus controlled for the effect of firm size, firm age, industry, IT investment, innovation investment, and quality management investment on firm performance as they can directly affect firm performance. We also controlled for these variables to check whether the impact of IT integration on firm performance, and the effect of knowledge absorptive and knowledge desorptive capacities on firm performance are kept after including these control variables. Firm size was measured by the natural logarithm of the number of employees in 2016 with information collected from Actualidad Economica database (Mithas et al. 2011, Benitez and[START_REF] Benitez | Information technology, the organizational capability of proactive corporate environmental strategy and firm performance: A resource-based analysis[END_REF]. Firm age was measured through the natural logarithm of the number of years the firm has been in the market in April-May 2016 [START_REF] Mithas | How information management capability influences firm performance[END_REF][START_REF] Benitez | How information technology influences opportunity exploration and exploitation firm's capabilities[END_REF]) by including a single-item question in the questionnaire about the number of years the firm has been in the market. Interindustry differences can also have an impact on the performance of the firm. We thus controlled for industry by measuring industry as a composite construct as follows. We classified industries in seven groups and identified the most important industry as the reference group (Benitez et al. 2018a[START_REF] Benitez | How to perform and report an impactful analysis using partial least squares: Guidelines for confirmatory and explanatory IS research[END_REF]. This group of reference was consumer goods. Then, we created for each observation six dummy indicators (industry group)

giving the value 0 if it does not pertain to this industry, and 1 if it does. Thus, industry was computed as a first-order composite construct composed by six indicators, that is, six group of industries [START_REF] Henseler | Using PLS path modeling in New Technology research: Updated guidelines[END_REF][START_REF] Benitez | How to perform and report an impactful analysis using partial least squares: Guidelines for confirmatory and explanatory IS research[END_REF]). We measured IT investment and innovation investment by asking each company the degree of annual IT investment and innovation investment on total turnover in the focal firm (1: Very low, 5: Very high). Quality management investment was measured with a single-item question that refers to the degree of implementation of quality management systems into the firm (1: Low implementation degree, 5: High implementation degree) [START_REF] Benitez | How information technology influences opportunity exploration and exploitation firm's capabilities[END_REF]).

Prevention and the test of common method variance

We also prevent and conduct the test of potential common method variance, although composite measures are unlikely to suffer from this bias [START_REF] Ronkko | PLS marker variable approach to diagnosing and controlling for method variance[END_REF]. First, we tried to prevent the appearance of common method variance in the research design. To do so, we guaranteed confidentiality and anonymity in the survey administration, respondents were not allowed to come back to prior questions, questions were not tagged, and were not given in the order hypothesized in the model [START_REF] Podsakoff | Common method biases in behavioral research: A critical review of the literature and recommended remedies[END_REF]. Second, we checked the correlation matrix to prevent high correlation among key variables (r > 0.90) [START_REF] Bagozzi | Assessing construct validity in organizational research[END_REF]). The highest correlation is 0.659.

Third, we checked variance inflation factor (VIF) values at construct level, given that VIF larger than 3.3 at construct level may alert about potential common method variance [START_REF] Kock | Lateral collinearity and misleading results in variance-based SEM: An illustration and recommendations[END_REF]. We estimated the VIF values at construct level by performing a full collinearity test. Values range from 1.055 to 1.961 for all constructs included in the model (Table 2). This suggests that it is unlikely that our research model suffers from common method variance [START_REF] Kock | Lateral collinearity and misleading results in variance-based SEM: An illustration and recommendations[END_REF].

All these tests taken together suggest that potential common method variance does not seem to be a problem in our study.

Empirical analysis and results

The proposed research model was empirically tested by performing a partial least squares (PLS) path modeling. PLS can test for exact overall model fit, and it is a full-fledged estimator in the family of variance-based structural equation modeling (SEM) [START_REF] Henseler | Using PLS path modeling in New Technology research: Updated guidelines[END_REF][START_REF] Rueda | From traditional education technologies to student satisfaction in Management education: A theory of the role of social media applications[END_REF][START_REF] Benitez | How to perform and report an impactful analysis using partial least squares: Guidelines for confirmatory and explanatory IS research[END_REF]). Using the PLS estimator is appropriate for the following reasons: 1) PLS is suitable to estimate composite models (as our proposed research model) [START_REF] Henseler | Common beliefs and reality about PLS: Comments on Ronkko and Evermann 2013[END_REF], 2016[START_REF] Rigdon | Conflating antecedents and formative indicators: A comment on Aguirre-Urreta and Marakas[END_REF], 2016); 2) PLS is particularly advisable for models that contain multidimensional constructs (as knowledge absorptive capacity and knowledge desorptive capacity in our study) [START_REF] Hair | An assessment of the use of partial least squares structural equation modeling in Marketing research[END_REF][START_REF] Hair | Rethinking some of the rethinking of partial least squares[END_REF]; 3) PLS is suitable when using new developed scales, as is the case in this study (knowledge desorptive capacity) (e.g., Chau 1997, Tiwana and[START_REF] Tiwana | Complementarities between organizational IT architecture and governance structure[END_REF]. Advanced Analysis for Composites (ADANCO) 2.0.1 Professional (http://www.composite-modeling.com/) was the statistical software used to estimate the measurement and structural models [START_REF] Henseler | ADANCO 2.0.1 Professional, Kleve, Composite Modeling[END_REF]. This software for variance-based SEM is able to model different types of constructs (i.e., composites, common factors, and singleindicator constructs) while facilitating both causal and predictive modeling [START_REF] Rueda | From traditional education technologies to student satisfaction in Management education: A theory of the role of social media applications[END_REF]).

Bootstrapping algorithm with 5000 subsamples was performed to obtain the level of significance of weights and loadings for each item and dimension, and to obtain the level of significance of path coefficients.

Confirmatory composite analysis

Every construct of the model (at first-and second-order level) was specified as composite. We used the weighting schemes of correlation weights (mode A) and regression weights (mode B) to estimate the research model. Both mode A and mode B create composite proxies [START_REF] Becker | Predictive validity and formative measurement in structural equation modeling: Embracing practical relevance[END_REF], Sarstedt et al. 2016). Correlation weights ignore collinearity among predictors; therefore it generates better estimations when there is a strong correlation between indicators [START_REF] Becker | Predictive validity and formative measurement in structural equation modeling: Embracing practical relevance[END_REF][START_REF] Rigdon | Choosing PLS path modeling as analytical method in European management research: A realist perspective[END_REF]. A composite-formative does not necessarily need to be estimated on mode B as there are certain conditions (e.g., multicollinearity) under which using mode A generates better weight estimations [START_REF] Becker | Predictive validity and formative measurement in structural equation modeling: Embracing practical relevance[END_REF]. Therefore, we used mode B for composites with noncorrelated indicators and mode A for composites with correlated indicators or unexpected signs in weights [START_REF] Benitez | How to perform and report an impactful analysis using partial least squares: Guidelines for confirmatory and explanatory IS research[END_REF]).

We performed a confirmatory composite analysis, which checks the adequacy of the measurement structure by comparing the empirical correlation matrix and the model-implied correlation matrix [START_REF] Henseler | Common beliefs and reality about PLS: Comments on Ronkko and Evermann 2013[END_REF][START_REF] Benitez | How information technology influences opportunity exploration and exploitation firm's capabilities[END_REF][START_REF] Benitez | How to perform and report an impactful analysis using partial least squares: Guidelines for confirmatory and explanatory IS research[END_REF]. It provides an overall model fit for the measurement structure at first-and second-order level by estimating the standardized root mean squared residual (SRMR), unweighted least squares discrepancy (dULS), and geodesic discrepancy (dG) [START_REF] Henseler | Common beliefs and reality about PLS: Comments on Ronkko and Evermann 2013[END_REF][START_REF] Henseler | Using PLS path modeling in New Technology research: Updated guidelines[END_REF]. SRMR is a proxy of the discrepancy between the empirical and the model-implied correlation matrix. The saturated model has good overall fit when SRMR is below 0.800. dULS and dG are exact measures of the overall model fit. The lower dULS and dG are, the better the model fit (Benitez et al. 2018a). dULS and dG values below the 99%-quantile of the bootstrap discrepancy shows acceptable fit between the model and the data [START_REF] Henseler | ADANCO 2.0.1. User Manual[END_REF][START_REF] Benitez | How to perform and report an impactful analysis using partial least squares: Guidelines for confirmatory and explanatory IS research[END_REF]. Table 3 shows results of the confirmatory composite analysis, which with 1% of probability gives support to the structure of our measures. Then, we proceed with the evaluation of the measurement model.

Measurement model evaluation

As knowledge absorptive capacity and knowledge desorptive capacity are two second-order constructs, we estimated the research model with the two-step approach [START_REF] Chin | How to write up and report PLS analyses[END_REF]. From the first step, latent variables' scores of the dimensions of knowledge absorptive capacity and knowledge desorptive capacity are obtained by freely correlating the first-order constructs and the dimensions of the second-order constructs (i.e., knowledge acquisition, knowledge assimilation, knowledge transformation, knowledge exploitation, knowledge identification, and knowledge transfer). We estimated the research model in the second step by using the latent variables' scores as the measures of the constructs knowledge absorptive capacity and knowledge desorptive capacity [START_REF] Chin | How to write up and report PLS analyses[END_REF].

We validated composite constructs by evaluating content validity, multicollinearity, and the significance of weights and loadings [START_REF] Cenfetelli | Interpretation of formative measurement in Information Systems research[END_REF]Bassellier 2009, Benitez et al. 2018b). First, we ensured content validity by using previously validated scales whenever possible (e.g., [START_REF] Pavlou | From IT leveraging competence to competitive advantage in turbulent environments: The case of new product development[END_REF]El Sawy 2006, Chen et al. 2017). This study develops a new scale of knowledge desorptive capacity using the information we extracted from seven interviews we did with IT/business executives as well as the preliminary conceptual foundations proposed in prior research (Lichtenthaler andLichtenthaler 2009, 2010).

We also evaluated multicollinearity and the significance of weights and loadings at first-and second-order levels. Multicollinearity may become a serious problem in the data if VIFs of indicators and dimensions are greater than 3.3 for constructs estimated in mode B [START_REF] Diamantopoulos | Formative versus reflective indicators in organizational measure development: A comparison and empirical illustration[END_REF]. VIFs values for constructs estimated in mode B range from 1.545 to 2.626 at first-order level and range from 1.129 to 1.986 at second-order level, below the threshold of 3.3.

We checked for the level of significance of indicator/dimension weights and loading. Composite indicators/dimensions can be retained as dropping indicators/dimensions may alter the composite's meaning (Henseler 2017a). Every first-and second-order loadings were significant at 0.001 level.

This analysis suggests good measurement properties. Table A1 (in the appendix) shows the measurement model evaluation. Next, we proceed with the evaluation of the structural model. which indicates the research model has the potential to be a good theory to explain how IT integration capability influences firm's knowledge absorption and desorption. After that, we can proceed with the evaluation of the structural model.

Evaluation of the structural model:

We evaluated path coefficients, the level of significance, R 2 , adjusted R 2 , and f 2 . We estimated two models: 1) the base model, which only includes the hypothesized relationships; and 2) the mediation model, where we add to the base model the direct effect of IT integration capability on firm performance. In the base model, we found support for hypotheses H1, H2, H3, H4, and H5, indicating that IT integration capability facilitates the development of a knowledge absorptive capacity (H1) (β = 0.487, pone-tailed < 0.001), and knowledge desorptive capacity (H2) (β = 0.391, pone-tailed < 0.001) to improve firm performance (H4) (β = 0.182, pone-tailed < 0.01) and (H5) (β = 0.251, pone-tailed < 0.05). H3 is also supported, indicating that knowledge absorptive capacity facilitates the development of knowledge desorptive capacity (H3) (β = 0.370, pone-tailed < 0.001). The effect of firm size, firm age, industry, IT investment, innovation investment, and quality management investment (control variables) on firm performance was not significant. However, the inclusion of these control variables gives additional credibility to the empirical analysis as it rechecks whether the effects of IT integration capability, knowledge absorptive capacity, and knowledge desorptive capacity on firm performance are sustained after controlling for these control variables.

The R 2 values range from 0.237 to 0.431, which suggests a good explanatory power of the endogenous variables. The adjusted R 2 values range from 0.231 to 0.423. The effect size value indicates the relative size of including each additional relationship to the model [START_REF] Benitez | How to perform and report an impactful analysis using partial least squares: Guidelines for confirmatory and explanatory IS research[END_REF]. f 2 values of the hypothesized relationships range from 0.028 to 0.311, indicating weakmedium to large effect sizes in the research model [START_REF] Cohen | Statistical power analysis for Behavioral Sciences[END_REF][START_REF] Benitez | How to perform and report an impactful analysis using partial least squares: Guidelines for confirmatory and explanatory IS research[END_REF]. Figure 2 and Table 4 present the results of the test of hypotheses. integration capability and firm performance. This mediation analysis shows that IT integration capability affects firm performance through knowledge absorptive capacity and knowledge desorptive capacity.

There are multiple mediators on this indirect effect (i.e., knowledge absorptive and knowledge desorptive capacities); therefore, a multiple mediation analysis can be used to clarify the effect of each variable on the mediation [START_REF] Cepeda | Mediation analyses in partial least squares structural equation modeling: Guidelines and empirical examples[END_REF]. Results indicate that there is indirect effect through knowledge absorptive capacity (β = 0.094, CI 7 [0.006, 0.181]) and knowledge desorptive capacity (β = 0.104, CI [0.024, 0.201]). The indirect effect of IT integration capability on firm performance through knowledge absorptive capacity [variance accounted for (VAF) = 0.453)] and through knowledge desorptive capacity (VAF = 0.504) demonstrates the great majority of the total indirect effect (VAF = 1.189). Additionally, we compared the two indirect effects (through knowledge absorptive capacity and through knowledge capacity) in a comparison analysis (Table 7). There are no significant differences between the two effects. This analysis suggests that the effects of knowledge absorptive capacity and knowledge desorptive capacity support the mediation equally. Tables 5,6, and 7 provide additional details of the mediation analysis. Note: † p < 0.10, * p < 0.05, ** p < 0.01, *** p < 0.001, one-tailed test for the indirect and total effect, two-tailed test for the direct effect.

7 CI: Confidence interval. The beta/effect is significant when zero is not included in the CI. Note: c': IT integration capability → Firm performance; a1xb1: IT integration capability → Knowledge absorptive capacity → Firm performance; a2xb2: IT integration capability → Knowledge desorptive capacity → Firm performance; a1xa3xb2: IT integration capability → Knowledge absorptive capacity → Knowledge desorptive capacity → Firm performance. We checked for the robustness of the proposed research theory by considering an alternative model in which knowledge desorptive capacity influences knowledge absorptive capacity but every other relationship remains the same. Results of this alternative model yield similar results to those obtained in the proposed model. The alternative model indicates that knowledge desorptive capacity is positively related to knowledge absorptive capacity (β = 0.419 *** ). This result indicates that it is also rational to think that firms may want to identify and transfer secondary knowledge first, and then, absorb core knowledge from the external firm as a knowledge management strategy.

This phenomenon can be explained by a situation in which the firm has to transfer some superficial knowledge to be able to obtain in return some core knowledge (again, pure opportunistic behavior).

Table A3 shows the details of this test of robustness.

That being said, we argue and propose in the proposed research model that companies with a leading IT integration capability should have developed a knowledge absorptive capacity prior to developing a knowledge desorptive capacity. Companies can develop the proficiency to identify superficial knowledge that can be useful and transferable to external partners once they have been created and stored in a substantial core and superficial knowledge base. The selection of superficial knowledge from a knowledge base also requires experience and a solid knowledge absorptive capacity. Anyway, this conceptual debate can be a "chicken-egg problem" theoretically.

Statistically, as our proposed research model (the model of Figure 2) does not have a statistically worse overall fit for the estimated model than the overall fit of the estimated alternative model (the model of the test of robustness), the alternative model is not preferred to our proposed research model [START_REF] Benitez | How to perform and report an impactful analysis using partial least squares: Guidelines for confirmatory and explanatory IS research[END_REF].

Finally, we also estimated a model where knowledge absorptive capacity and knowledge desorptive capacity freely correlate in the proposed research model (i.e., no relationship between knowledge absorptive capacity and knowledge desorptive capacity was included), and a model in which knowledge absorptive and knowledge desorptive capacities shape a third-order construct called knowledge management capability [START_REF] Tanriverdi | Information technology relatedness, knowledge management capability, and performance of multibusiness firms[END_REF]. These models yield similar results to those obtained in the proposed model (β IT integration capability → Knowledge management capability = 0.602 *** , β Knowledge management capability → Firm performance = 0.383 *** ). In conclusion, the results of this test of robustness provide additional credibility to the support of our research model and the findings presented in this study.

Importance-performance map analysis:

We performed an importance-performance map analysis (IPMA) at construct and dimension level to identify the antecedents that may have a high importance (i.e., those that have a strong total effect) for our key outcome construct (i.e., firm performance) and a high performance (i.e., those companies that perform well) [START_REF] Ringle | Gain more insight from your PLS-SEM results: The importance-performance map analysis[END_REF]. At construct level, we find knowledge absorptive capacity and knowledge desorptive capacity in very similar positions. Both constructs have similar performance values8 and above average importance values. That is, in absolute terms, when knowledge absorptive capacity is increased by one, firm performance will increase by the construct's importance (i.e., 0.314) (ceteris-paribus). In a similar way, when knowledge desorptive capacity is increased by one, firm performance will increase by 0.280 (ceteris-paribus).

At the dimension level, we find that knowledge transfer capability (i.e., one of the dimensions of knowledge desorptive capacity) has high importance value (i.e., above average), while it has the lowest performance value (68.155). That means companies need to improve the performance of knowledge transfer capability given that its importance for firm performance is significant. We also find knowledge acquisition capacity and knowledge exploitation capacity (i.e., two dimensions of knowledge absorptive capacity construct) and knowledge identification capacity (i.e., one dimension of knowledge desorptive capacity construct) in the high performance and high importance values quadrant, which indicates that they have important and significant effect on firm performance. Finally, we find knowledge assimilation capacity and knowledge transformation capacity (i.e., two dimensions of knowledge absorptive capacity) in the quadrant with low importance values and low performance values (i.e., below average), deriving that those variables are not a priority for companies due to the low significant effect on firm performance. Figures 3 and4 show the IPMA at both constructs and dimension levels.

Discussion and conclusions

How does the firm's IT integration capability in the supply chain affect knowledge absorption and desorption of the focal firm? This is the cutting edge and idiosyncratic research question this study aims to study theoretically and investigate empirically. Drawn from prior IS research on IT and knowledge management (Tanriverdi 2005, Dong and[START_REF] Dong | Information technology and organizational learning in knowledge alliances and networks: Evidence from U.S. pharmaceutical industry[END_REF] and on the IT-enabled organizational capabilities perspective [START_REF] Mithas | How information management capability influences firm performance[END_REF], Benitez et al. 2018a[START_REF] Benitez | IT-enabled knowledge ambidexterity and innovation performance in small U.S. firms: The moderator role of social media capability[END_REF], we theorized that the firm's ability to integrate its IT systems with the IT systems of external partners (IT integration capability in an interorganizational relationships context) enables the focal firm to absorb core knowledge and desorb superficial knowledge to generate business benefits. The proposed theory was tested on a sample of firms in Spain. The empirical analysis gave support to the proposed theory.

Prior research lacks the overall understanding about how IT matters in the key knowledge management capabilities for the focal firm and its supply chain. Specifically, research has been limited to study how desorptive capacity contributes to supply chain competitiveness [START_REF] Roldan | Examining desorptive capacity in supply chains: The role of organizational ambidexterity[END_REF] or how IT capabilities affect absorptive capacity either directly or indirectly (Liu et al. 2013, Figure 4: IPMA analysis at dimension level [START_REF] Limaj | The impact of social information system governance, utilization, and capabilities on absorptive capacity and innovation: A case of Austrian SMEs[END_REF], lacking to show how firm's IT investments affect the whole picture of knowledge management activities.

How does a firm's IT integration capability affect knowledge management capabilities to create business value? The IT integration capability enables the focal firm the development of knowledge absorptive capacity and knowledge desorptive capacity, which in turn helps the focal firm to improve firm performance. The integration of the IT systems of the focal firm with the IT systems of others organizations of the firm's supply chain facilitates the integration of supply chain information, and access and sharing of order-related data, production-related data, customer-related data, and market-related data as well as the coordination of the business activities between the focal firm and the external organizations. This information integration, data access and sharing, and business activity coordination enables the knowledge acquisition, assimilation, transformation, and exploitation of external core knowledge (knowledge absorption of the focal firm) for commercial ends [START_REF] Cohen | Statistical power analysis for Behavioral Sciences[END_REF]Levinthal 1990, Zahra andGeorge 2002). Once the focal firm has absorbed sufficient degree of external core knowledge is interested in transferring superficial knowledge to other external organizations to obtain a licensing income, entry into a foreign market, or access to future core knowledge from these external partners. In this sense, we argue that knowledge absorption leads to knowledge desorption. Both knowledge absorption and knowledge desorption improve firm performance and create business value. The investments in IT integration capability are thus converted into business benefits through the absorption and desorption of knowledge, which is consistent with the prior theory building on the IT-enabled organizational capabilities perspective.

This research provides two key contributions to the IS discipline. First, this study introduces the construct of knowledge desorptive capacity in the IS research and provides a scale for its measure.

Knowledge desorptive capacity is the ability of the firm to identify and transfer its knowledge to external partners [START_REF] Lichtenthaler | Technology transfer across organizational boundaries: Absorptive capacity and desorptive capacity[END_REF]. The concept of knowledge desorptive capacity was presented by [START_REF] Lichtenthaler | A capability-based framework for open innovation: Complementing absorptive capacity[END_REF]. We develop theoretically this construct by adding the superficial/secondary nature of the knowledge desorbed by firms. We argue that firms should not be interested in desorbing core knowledge. In addition, this construct lacked a set of validated measures. We introduce the construct of knowledge desorptive capacity to IS research into a business value of IT conversation, and provide a set of calibrated measures at first-and second-order level that can be used by future IS scholars. This is the primary contribution of this paper to IS research.

Second, this research provides and demonstrated a theory of IT integration impact on the firm's knowledge absorption and desorption, and their impact on firm performance. Prior IS research has focused on studying the impact of IT on knowledge absorption (e.g., [START_REF] Joshi | Changing the competitive landscape: Continuous innovation through IT-enabled knowledge capabilities[END_REF][START_REF] Liu | The impact of IT capabilities on firm performance: The mediating roles of absorptive capacity and supply chain agility[END_REF]), but the focus on the role of IT in knowledge desorption has not been examined. We develop the body of IS research on IT and knowledge management activities at firm level [START_REF] Tanriverdi | Information technology relatedness, knowledge management capability, and performance of multibusiness firms[END_REF] We often scan the environment to identify knowledge that could be relevant to our customers 1.545 0.638 *** 0.922 ***

We often scan the environment to identify knowledge that could be

Figure

  Figure 1: The research model

  Knowledge absorptive capacity was measured as a second-order composite construct composed by four first-order dimensions: knowledge acquisition, knowledge assimilation, knowledge transformation, and knowledge exploitation(Zahra and George 2002[START_REF] Pavlou | From IT leveraging competence to competitive advantage in turbulent environments: The case of new product development[END_REF][START_REF] Liu | The impact of IT capabilities on firm performance: The mediating roles of absorptive capacity and supply chain agility[END_REF]. We used a well-established and validated scale by adapting the scales from[START_REF] Pavlou | From IT leveraging competence to competitive advantage in turbulent environments: The case of new product development[END_REF],[START_REF] Liu | The impact of IT capabilities on firm performance: The mediating roles of absorptive capacity and supply chain agility[END_REF], and[START_REF] Setia | How information systems help create OM capabilities: Consequences and antecedents of operational absorptive capacity[END_REF]. Knowledge acquisition evaluates in a five-item scale the ability to identify external knowledge that could be relevant to the firm[START_REF] Pavlou | From IT leveraging competence to competitive advantage in turbulent environments: The case of new product development[END_REF][START_REF] Liu | The impact of IT capabilities on firm performance: The mediating roles of absorptive capacity and supply chain agility[END_REF][START_REF] Setia | How information systems help create OM capabilities: Consequences and antecedents of operational absorptive capacity[END_REF]. Knowledge assimilation measures in a three-item scale the ability to understand new knowledge[START_REF] Pavlou | From IT leveraging competence to competitive advantage in turbulent environments: The case of new product development[END_REF] El Sawy 2006, Liu et al. 2013). Knowledge transformation

  fit of the estimated model: As in the confirmatory composite analysis, the goodness of model fit for the structural model (estimated model) was evaluated by examining the SRMR, dULS, and dG[START_REF] Benitez | How to perform and report an impactful analysis using partial least squares: Guidelines for confirmatory and explanatory IS research[END_REF]). The SRMR value for the base model (i.e., excluding the direct effects of the mediation analysis) is 0.065, and discrepancy values are below the 95%-quantile of the bootstrap discrepancies, which suggests our base research model should not be rejected based on the alpha level of 0.05. Overall, the proposed research model shows good structural model fit,

Figure 2 :

 2 Figure 2: Results of the PLS estimation

  management investment → Firm performance (control variable)

Figure 3 :

 3 Figure 3: IPMA analysis at construct level

  recommendations about internal processes to external agents (e.g., suppliers and customers) 1.945 0.223 *** 0.790 *** We often transfer information about our strategies to external agents (e.g., suppliers and customers) 2.764 0.237 *** 0.815 *** We often transfer information about the product or the market to external agents (e.g., suppliers and customers) 3.619 0.206 *** 0.820 *** The transfer of knowledge to external agents (e.g., suppliers, customers, and other organizations) is organized well 3.046 0.240 *** 0.861 *** Firm performance: Rate the extent to which the firm has achieved the following outcomes during the last two years (compositep < 0.10, * p < 0.05, ** p < 0.01, *** p < 0.001, two-tailed test.

  and that usually invested in IT and social media[START_REF] Kane | Moving beyond marketing: Generating social business value across the Enterprise[END_REF]) from the 5000 most admired firms included in the Actualidad All possible t-test comparisons between the means of the two groups of respondents showed nonsignificant differences. On average, the total revenues of the sample firms in 2016 were 121.080 million Euros, and they had about 677 employees.Before performing the empirical analysis, we checked the minimum sample size required to test the proposed research model. Assuming an anticipated medium effect size, a statistical power level of 0.800, an alpha of 0.05, and nine indicators (i.e., the largest number of structural paths directed

	by senior marketing executives (Chief Marketing Officer, Marketing Vice President, Marketing
	Manager, and Community Manager) (50.330%), IT executives (Chief Information Officer, IT Vice
	President, and IT Manager) (23.180%), and other business executives (New Product Development
	Executive, Chief Executive Officer, Operations Vice President, Corporate Development Officer,
	and Human Resource Manager) (26.500%). We also asked the key informants for a self-evaluation
	of their degree of knowledge in answering the survey. The item "How knowledgeable did you feel
	in answering all the questions included in this questionnaire?" (1: Very low, 5: Very high) was
	included at the end of the questionnaire (Tanriverdi 2005). The average value for this item was
	3.830 (S.D.: 0.810), which suggests that the key informants had a high level of competence to
	answer the questions included in the survey.
	The questionnaire was designed by adapting scales from prior literature and pretested with seven
	IT/business executives. As prior literature had not developed and studied a scale for knowledge
	desorptive capacity, we carefully developed a new scale. In fact, this is one of the potential
	contributions of this paper. We employed a key knowledgeable informant per firm to answer the
	questions included in the questionnaire (Table A1 in the appendix). Questionnaires were completed

Economica database in 2015: consumer goods, manufacturing, automotive, entertainment, chemical, information and communications, healthcare services, education, and professional services. In this sense, a population of 1826 large Spanish firms was selected. From the list of 1826 firms, 934 were contacted by phone through a well-established consulting vendor. The consulting vendor finally received 151 valid questionnaires from April 5, 2016 to May 18, 2016, giving an effective response rate of 16.167%, which is similar to the response rate obtained in prior IS research

(Benitez et al. 2018a

) can be considered as satisfactory especially if we recognize the cost and degree of difficulty of accessing top IT and business executives. In this regard, the sample of this study is composed by 151 firms from seven industries: 47 firms (31.130%) operated in the consumer goods, 32 (21.190%) in manufacturing, 21 (13.910%) in automotive, 19 (12.580%) in entertainment, 13 (8.610%) in chemical, 11 (7.280%) in information and communications, and the rest (eight firms, 5.300%) in other industries (i.e., healthcare services, education, and professional services). Non-response bias was assessed by verifying that early and late respondents did not differ in their responses. We considered as early respondents any of the firms that responded to the questionnaire in the first four weeks.

to firm performance in our mediation model), the minimum required sample size to test the statistical significance of the relationships of the research model is 114

[START_REF] Nitzl | The use of partial least squares structural equation modelling (PLS-SEM) in Management Accounting research: Directions for future theory development[END_REF]

). As our sample size is 151, we have an acceptable sample size to test the proposed research model.

We use survey data to measure IT integration capability, knowledge absorptive capacity, knowledge desorptive capacity, firm performance, firm age (control variable), IT investment (control variable), innovation investment (control variable), and quality management investment (control variable). Firm size and industry (control variables) were measured with archival data collected from Actualidad Economica database in 2015.

Table 2 : Full collinearity test

 2

	Construct	VIF values
	IT integration capability	1.757
	Knowledge absorptive capacity	1.792
	Knowledge desorptive capacity	1.961
	Firm performance	1.373
	Firm size	1.133
	Firm age	1.131
	Industry	1.223
	IT investment	1.914
	Innovation investment	1.881
	Quality management investment	1.055

Table 3 : Results of the confirmatory composite analysis

 3

		First-order		Second-order
	Discrepancy	constructs		constructs
		Value HI99	Conclusion	Value	HI99	Conclusion
	SRMR	0.064 0.064	Supported	0.023	0.050	Supported
	dULS	2.450 2.499	Supported	0.011	0.052	Supported
	dG	1.037 1.526	Supported	0.010	0.032	Supported

Table 4 : Evaluation of the structural model Beta coefficient Base model Mediation model

 4

		0.487 ***	0.488 ***
	IT integration capability → Knowledge absorptive capacity (H1)	(6.378) 5 (0.000)	(6.405) (0.000)
		[0.354, 0.613]	[0.359, 0.614]
		0.391 ***	0.392 ***
	IT integration capability → Knowledge desorptive capacity (H2)	(5.150) (0.000)	(5.165) (0.000)
		[0.262, 0.512]	[0.260, 0.510]
		0.370 ***	0.369 ***
	Knowledge absorptive capacity → Knowledge desorptive capacity (H3)	(6.071) (0.000)	(6.092) (0.000)
		[0.273, 0.470]	[0.272, 0.469]
	Knowledge absorptive capacity → Firm performance (H4)	0.182 * (1.724)	0.192 * (1.844)

5

This value refers to the t-value. The value that appears below refers to the p-value.

Table 5 : Mediation analysis

 5

	Relationship	Direct effect	Indirect effect	Total effect
		-0.039	0.246 **	0.207 *
	IT integration capability → Firm	(-0.334)	(3.227)	(2.488)
	performance	(0.739)	(0.001)	(0.006)
		[-0.264, 0.194]	[0.130, 0.367]	[0.068, 0.343]

Table 6 : Multiple mediation effects

 6

		Coefficient		Bootstrap 90% CI
			Percentile	Biased corrected (BC)
	Direct effects
	a1	0.488	0.357	0.612	0.359	0.614
	a2	0.392	0.257	0.507	0.260	0.510
	a3	0.369	0.276	0.473	0.272	0.469
	b1	0.192	0.009	0.358	0.011	0.360
	b2	0.266	0.071	0.456	0.070	0.455
	Indirect effects
			Percentile	BC		VAF
	a1xb1	0.094	0.005	0.179	0.006	0.181	0.453
	a2xb2	0.104	0.024	0.200	0.024	0.201	0.504
	a1xa3xb2	0.048	0.012	0.092	0.011	0.092	0.232
	Total indirect effect	0.246	0.129	0.366	0.130	0.367	1.189

Table 7 : Indirect effects comparison Coefficient Bootstrap 95% CI Differential effect Percentile BC

 7 Our PLS estimation of the proposed research model can be complemented with a test of robustness to examine alternative relationships and conceptual models.

	M1 -M2 = a1xb1 -a2xb2	-0.011	-0.192	0.153	-0.188	0.157
	4.3.4. Test of robustness:

,

  [START_REF] Pavlou | From IT leveraging competence to competitive advantage in turbulent environments: The case of new product development[END_REF]) by both theorizing and testing empirically the impact of IT integration capability on both knowledge absorption and desorption. The findings of our study also have core theoretical implications for IS research on business value of IT and the IT-enabled organizational capabilities perspective. Our theory building sets IT integration capability effects on firm performance through the capability development of knowledge absorption and knowledge desorption. In this sense, knowledge absorptive capacity and knowledge desorptive capacity are two intermediate organizational capabilities through which IT affects firm performance. This is the second primary contribution of this research to IS research.This study has also limitations. First, as business value of IT studies is mostly focused in U.S. and U.K. firms (e.g.,Benitez et al. 2018a), and because Spain is a critical market of the European Union with a high volume of firm's IT initiatives, this study was contextualized in large firms in Spain. For this reason, the results should only be generalized to large firms in Spain. Future research should explore whether our findings are also valid in other markets worldwide, and whether this theory is supported in small and medium firms. Second, the key endogenous variable was assessed through a perceptual measure of firm performance. Although our empirical analysis was prevented and checked from potential common method bias, we encourage IS scholars to continue this line of research by measuring business benefits with archival data. Although using two key respondents per firm has been suggested to rigorously execute IS research on business value of IT, this kind of research design is often very difficult to obtain and very costly. Third, in regard to most of the research projects and estimations, our study was developed with assumptions. Based on[START_REF] Gupta | Knowledge flows within multinational corporations[END_REF] work, our study assumes that organizations exhibit an opportunistic behavior because they play "the game of coopetition" with other organizations by trying to absorb core knowledge but only desorbing secondary knowledge. Future IS research could examine if this assumption is correct. We also recognize that the relationship between knowledge absorptive capacity and knowledge desorptive capacity may suffer from a "chicken-egg problem." However, our empirical analysis and findings are not affected if the opposite effect (Knowledge desorptive capacity → Knowledge absorptive capacity) is included in the model; similarly, the results obtained in this research are not affected when we allow these two constructs to be freely correlated. Future IS research should focus specifically in discovering the preferred sequence companies follow in absorbing and desorbing knowledge.IS research on knowledge desorption is extraordinarily scarce. In this sense, this topic presents different avenues for future research: First, firms and executives have received high pressure from competitors, employees, and customers to implement digital transformation programs, which represents a good opportunity for companies to absorb and desorb critical knowledge from their innovation ecosystem. Future IS research could examine the role of knowledge absorptive and knowledge desorptive capacities of the focal firm for the successful implementation of the digital transformation programs. We believe this line of IS research will bring very promising research Knowledge absorptive capacity implies both the acquisition and exploitation of knowledge (Zahra and George 2002), which suggests a certain degree of ambidexterity. At the same time, once firms have absorbed a sufficient degree of external core knowledge, they are interested in desorbing and commercializing with secondary knowledge to better exploit and capitalize their knowledge base and maximize business benefits. The findings that are derived from our research may suggest in a preliminary way that there can exist several levels of organizational ambidexterity in the firm, that is, different degrees of ambidexterity in different types of organizational capabilities, as illustrated in this study in knowledge absorptive capacity and knowledge desorptive capacity. Future IS research should examine this preliminary insight, which seems to be an excellent avenue for future empirical IS research. All these IS topics promise to come with excellent research questions, challenging research designs, and potentially interesting discussions for the IS research community.Worldwide IT investment is projected to total $3.8 trillion in 2019 and a significant percentage of this worldwide investment is firm's IT investments at the supply chain level. As companies and top IT executives need to motivate and show the return from their IT investments, this study provides three very useful lessons to IT executives. First, firms can capitalize their investments in IT systems integration in the supply chain because it facilitates the focal firm to absorb core knowledge and desorb secondary knowledge from other organizations to generate business benefits. In this sense, assuming an opportunistic behavior of the focal firm in its knowledge transfer activities, we show how firms can create business value from IT integration through knowledge absorption and desorption. Second, this study also focuses and shows IT executives how critical it is to purposely design first the firm's absorption activities of core knowledge, and therefore focusing on the firm's desorption activities of secondary knowledge. Finally, this study also provides IT executives the guidelines and measures to evaluate their degree of knowledge absorptive capacity by providing a set of calibrated fine-grained measures of knowledge absorptive capacity.

	practices on lead-time performance. Decision Sciences 37(2), 177-203.
	Wu, S., Melnyk, S., and Flynn, B. (2010). Operational capabilities: The secret ingredient. Decision
	Sciences 41(4), 721-754.
	Zahra, S., and George, G. (2002). Absorptive capacity: A review, reconceptualization, and
	extension. Academy of Management Review 27(2), 185-203.
	Zhao, X., Lynch, J., and Chen, Q. (2010). Reconsidering Baron and Kenny: Myths and truths about
	mediation analysis. Journal of Consumer Research 37(2), 97-206.
	7. Appendix
	As final concluding remarks, this research examines how the firm's IT integration capability in
	the supply chain affects knowledge absorption and desorption. We theorized that the IT integration
	capability enables the focal firm to absorb core knowledge and desorb secondary knowledge, which
	in turn improves firm performance. Our proposed research theory assumes an opportunistic
	behavior among companies that try to absorb primary knowledge but transfer secondary
	knowledge. We tested the proposed theory with a sample of large firms in Spain. After preventing
	and checking for common method variance, and testing several alternative research models, the
	empirical analysis gives support to our theory. This paper develops IS research on business value
	of IT by introducing the construct of knowledge desorptive capacity (and a set of calibrated
	measures), and by providing and testing a theory on the role of IT integration in knowledge
	absorption and knowledge desorption. In this sense, IT does matter because it creates business
	value. It is a great time to be an IS scholar but a challenging/changing/disruptive time to be an IT
	executive. Quo Vadis?

results, theory building, and success to IS scholars. Second, firms may participate in collaboration networks (with competitors and the competitor's allies) to compete better by absorbing core knowledge and desorbing secondary knowledge. However, this implies an opportunistic behavior that can be deployed only for a limited period of time until other organizations discover this opportunistic behavior. We encourage IS scholars to explore how this past opportunistic behavior driven by the simultaneous usage of knowledge absorption and desorption affects the firm's reputation in a collaborative network and future business benefits of the focal firm.

Finally, organizational ambidexterity implies the firm's ability to simultaneously explore and exploit the knowledge

[START_REF] Benitez | IT-enabled knowledge ambidexterity and innovation performance in small U.S. firms: The moderator role of social media capability[END_REF]

) of business opportunities

[START_REF] Benitez | How information technology influences opportunity exploration and exploitation firm's capabilities[END_REF]

).

Table A1 : Detailed information on survey items

 A1 We are able to organize special meetings with suppliers, customers, or third parties to acquire new knowledge on process, product,

		2.618	0.240 *** 0.853 ***
	logistics and distribution related to innovation
	We are able to identify and acquire internal (i.e., within the firm) and external (e.g., market) knowledge	2.434	0.307 *** 0.856 ***
	We are successful in learning new things	1.501	0.322 *** 0.763 ***
	Knowledge assimilation (composite, mode A)	1.697	0.298 *** 0.787 ***
	We quickly analyze and interpret changing market demands	2.674	0.342 *** 0.901 ***
	We have adequate routines to analyze the information and knowledge obtained	3.317	0.352 *** 0.926 ***
	Construct/indicator: Except where otherwise indicated below, the We have adequate routines to assimilate new information and knowledge	3.138	0.394 *** 0.929 ***
	possible range for measures was from 1 to 5 (1: Strongly disagree, Knowledge transformation (composite, mode A)	VIF 2.455	Weight Loading 0.326 *** 0.881 ***
	5: Strongly agree) IT integration capability (composite, mode A) We are effective in transforming existing information into new knowledge	3.802	0.311 *** 0.880 ***
	Our IT systems enable us integrated access and sharing of all order-related data (e.g., order status, handling requirements, etc.) We can successfully integrate the new information and knowledge acquired with our existing knowledge	1.576 4.200	0.203 *** 0.716 *** 0.327 *** 0.912 ***
	Our IT systems enable us integrated access and sharing of all production-related data (e.g., resource availability, quality, etc.) Our firm quickly recognizes the usefulness of new external knowledge to existing knowledge	1.989 1.953	0.255 *** 0.820 *** 0.269 *** 0.823 ***
	Our IT systems enable us integrated access and sharing of all customer-related data (e.g., service contracts, feedback, etc.) Our firm periodically meets to discuss consequences of market trends and new product development	2.187 1.460	0.193 *** 0.767 *** 0.286 *** 0.720 ***
	Our IT systems enable us integrated access and sharing of all Knowledge exploitation (composite, mode B) market-related data (e.g., promotion details, future forecasts, etc.) To what extent do your IT systems facilitate coordinated activities with external agents (e.g., suppliers, customers, other We can successfully exploit the new integrated information and knowledge into concrete applications Our firm has a clear division of roles and responsibilities	2.839 1.986 1.776 1.573 2.626	0.301 *** 0.820 *** 0.297 *** 0.875 *** 0.454 *** 0.848 *** 0.300 *** 0.793 *** 0.085 0.791 ***
	organizations)? (1: Very low, 5: Very high) We are effective in applying knowledge into new products	2.601	0.319 * 0.855 ***
	Knowledge absorptive capacity (second-order construct, We constantly consider better ways to exploit knowledge	2.917	0.316 * 0.872 ***
	composite, mode A) Knowledge acquisition (composite, mode A) Knowledge desorptive capacity (second-order construct, composite, mode B)	1.709	0.289 *** 0.197 ***
	We are effective in developing new knowledge or insights that have Knowledge identification (composite, mode B) the potential to influence new product development Our employees are engaged in cross-functional teams We often scan the environment to identify knowledge that could be relevant to our suppliers	1.272 1.129 1.772 2.143	0.207 *** 0.606 *** 0.754 *** 0.906 *** 0.211 *** 0.758 *** 0.217 0.781 ***

Table A2 : Correlation matrix

 A2

	Construct	1	2	3	4	5	6	7	8	9	10
	1. IT integration capability 1.000
	2. Knowledge absorptive capacity	0.487 1.000
	3. Knowledge desorptive capacity	0.571 0.560 1.000
	4. Firm performance	0.201 0.366 0.382 1.000
	5. Firm size	0.114 0.179 0.210 0.030 1.000
	6. Firm age	-0.226 0.043 -0.168 -0.004 -0.014 1.000
	7. Industry	-0.028 0.112 0.104 0.344 -0.186 0.008 1.000
	8. IT investment	0.312 0.306 0.248 0.122 0.182 -0.039 -0.007 1.000
	9. Innovation investment	0.241 0.294 0.198 0.120 0.140 -0.101 -0.054 0.659 1.000
	10. Quality management investment	0.082 0.013 -0.020 0.040 -0.056 -0.066 -0.074 -0.003 0.118 1.000

Table A3 : Results of the test of robustness

 A3

		[-0.003, 0.353]	[0.020, 0.359]
		0.251 **	0.266 *
	Knowledge desorptive capacity → Firm performance (H5)	(2.561) (0.005)	(2.231) (0.013)
		[0.090, 0.411]	[0.065, 0.458]
			-0.039
	IT integration capability → Firm performance		(-0.334) (0.739)
			[-0.264, 0.194]
	Control variables
		0.003	0.001
	Firm size → Firm performance (control variable)	(0.044) (0.965)	(0.012) (0.990)
		[-0.130, 0.139]	[-0.131, 0.140]
		0.036	0.029
	Firm age → Firm performance (control variable)	(0.493) (0.622)	(0.404) (0.686)
	Beta coefficient IT integration capability → Knowledge absorptive capacity (H1) Industry → Firm performance (control variable)	Base model [-0.100, 0.182] 0.248 ** (2.681) (0.004) [0.090, 0.398] 0.304 (0.900) (0.368) [-0.475, 0.459]	[-0.107, 0.177] Mediation model 0.300 0.248 ** (2.696) (0.897) (0.370) (0.004) [0.093, 0.400] [-0.467, 0.451]
	IT integration capability → Knowledge desorptive capacity (H2) IT investment → Firm performance (control variable)	0.571 *** (9.847) (0.000) [0.465, 0.665] -0.020 (-0.204) (0.839) [-0.219, 0.175]	-0.012 0.572 *** (9.871) (-0.122) (0.903) (0.000) [0.465, 0.664] [-0.211, 0.181]
	Knowledge desorptive capacity → Knowledge absorptive capacity (H3) Innovation investment → Firm performance (control variable)	0.419 *** (6.380) (0.000) [0.310, 0.528] 0.042 (0.455) (0.649) [-0.139, 0.221]	0.039 0.418 *** (6.378) (0.365) (0.671) (0.000) [0.308, 0.529] [-0.142, 0.220]
	Knowledge absorptive capacity → Firm performance (H4) Quality management investment → Firm performance (control variable)	0.182 * (1.724) (0.042) 0.062 (0.909) (0.364) [-0.078, 0.196]	0.065 0.192 * (0.935) (1.844) (0.350) (0.033) [-0.075, 0.199]
	48

This study focuses on IT integration capability and its role on the firm's knowledge absorption and desorption. However, we use the terms IT integration capability and IT integration interchangeably for the sake of brevity. The terms capability and capacity are also used interchangeably in this paper.

This study uses the term core knowledge and primary knowledge interchangeably. Core knowledge refers to knowledge that can make the firm special for the customer. Examples of this core knowledge are knowledge on innovative processes and products, know-how, distribution, logistics, and on a disruptive technology. Similarly, this research uses superficial and secondary knowledge interchangeably. Secondary knowledge refers to knowledge that does not have the potential to make the firm special for the customer. Examples of this secondary knowledge are knowledge on operational routines, scheduling, soft technology, and nonrelevant products and suppliers. Our research was developed under the theoretical assumption that organizations exhibit an opportunistic behavior because they play "the game of coopetition" with other organizations by trying to absorb core knowledge but only desorbing secondary knowledge. Our assumption is consistent with the work of[START_REF] Gupta | Knowledge flows within multinational corporations[END_REF]. Although this assumption might be difficult to prove empirically, we believe it is very rational given the hypercompetition of the current business landscape.

Based on[START_REF] Lichtenthaler | A capability-based framework for open innovation: Complementing absorptive capacity[END_REF] work, they argue that while knowledge absorptive capacity is mainly related to exploration activities, knowledge desorptive capacity is mainly related to exploitation activities (e.g., business benefits and entering into a new market). However, we recognize that both exploration and exploitation activities might exist in both knowledge absorptive capacity and knowledge desorptive capacity. This would potentially suggest that different levels of ambidexterity might exist in companies in different organizational capabilities such as knowledge absorptive capacity and knowledge desorptive capacity (please see our future research directions on this topic). We thank the anonymous Reviewer 4 for his/her recommendations on this issue.

The beta coefficient between IT integration capability and firm performance (-0.039), and the correlation between both variables (0.201) have different sign, which reflects random fluctuations around zero[START_REF] Falk | A primer for soft modeling[END_REF].

Given that both knowledge absorptive capacity and knowledge desorptive capacity are located close to the horizontal center line, we should regard these placements cautiously and not as definite (Henseler forthcoming).

This research was sponsored by the European Regional Development Fund (European Union) and the Government of Spain (Research Project ECO2017-84138-P, and Research Grants FPU13/01643 and FPU18/01405), the Regional Government of Andalusia (Research Project P11-SEJ-7294), the COVIRAN-Prodware Endowed Chair of Digital Human Resource Strategy at the University of Granada, the Endowed Chair of Business Value of IT of the Green, Digital, and Demand-driven Supply Chain Management Excellence Area at Rennes School of Business, and the Slovenian Research Agency (Research Core Funding No. P5-0410).