Shen Xu
email: s.xu@pgr.reading.ac.uk

Kecheng Liu
email: k.liu@henley.ac.uk

Llewellyn Cm Tang
email: llewellyn.tang@nottingham.edu.cn

Applying Organizational Semiotics for Developing Knowledge-Based Cost Estimation of Construction Project

Keywords: analytical cost estimation, knowledge representation, information system development, industry foundation classes, quantity surveying

des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

Introduction

An exploration and analysis of various BIM-5D applications confirmed observations in the literature that model-based construction cost estimation need a new method that could meet the need to core cost estimating workflows [START_REF] Skidmore | Merrill Standardizes Freedom Tower Project on Autodesk Revit Platform[END_REF][START_REF]Bentley Review and Study of the Opera Theater Interior and New Works[END_REF][START_REF]Graphisoft World's Tallest Residential Tower Designed with 3D Virtual Building Concept[END_REF]. Because in addition to material quantities, product features, such as openings and repetition, also affect construction costs [START_REF] Kiziltas | Contextual information requirements of cost estimators from past construction projects[END_REF]. Previously such factors are being considered by expert into the adjustment of estimation [START_REF] Ashworth | s Practice and Procedure for the Quantity Surveyor[END_REF]. This approach is often difficult to integrate into current computing practices because it is a 'black box' and difficult for computer to understand [START_REF] Staub | Practical and research issues in using Industry Foundation Classes for construction cost estimating[END_REF]. Therefore, existing software tools do not explicitly capture quantity surveyors' rationale for how the component properties and product features affect the cost information and cost estimation requires contextual information and current support is insufficient for this requirement [START_REF] Kiziltas | Contextual information requirements of cost estimators from past construction projects[END_REF]. Meanwhile, conventional programming language is insufficient to deal with certain estimating activities for example comply with standard, which is an essential requirement for costing practitioner.

Existing knowledge engineering process produces ontology, in the form of classification systems and product data models, lacks effective modelling of concept semantics and related pragmatics: a fundamental requirement for human-based exchange of knowledge [START_REF] El-Diraby | Domain taxonomy for construction concepts: toward a formal ontology for construction knowledge[END_REF]. Being investigated into human reasoning processing, more specific, the cost estimating process consists of locating objective information, recognizing it in the immediate situation or in the past, evaluating the objective information, combining the information together, and then implementing it as a certain value of estimation. With the development of information technology, locating objective information is helped by using a search engine, recognizing objective information in the immediate situation or in the past is facilitated by cost database (cost index). However, by lacking a knowledge model of cost estimation which integrates domain semantic and pragmatics, the issues remain the same, firstly time is insufficient for doing cost estimation [START_REF] Akintoye | A survey of current cost estimating practices in the UK[END_REF], secondly we are hardly able to find the valuable information [START_REF] Ashworth | s Practice and Procedure for the Quantity Surveyor[END_REF], thirdly, cost estimation requires contextual information [START_REF] Kiziltas | Contextual information requirements of cost estimators from past construction projects[END_REF].

Furthermore the general idea is that data and services are semantically described with respect to knowledge representation language, which are formal specifications of a domain of interest, and can thus be shared and reused in a way such that the shared meaning specified remains formally the same across different parties and applications. Then a business process is being modelled with norms in order to capture the application logic. Finally a special purpose reasoning engine could be employed, based on logic programming that operates on the above two structures in an integrated way. The paper has been structured as follows: we firstly study the advantage of applying the framework, in which corresponding to the knowledge capturing problem in quantity surveying organization. Then the results of pilot study have been demonstrated to show feasibility of introduced approach. Finally conclusion and future research is presented.

Semiotics in Construction Domain

While the development of information technology, many software applications, for instance Sage Timberline [START_REF]Sage Sage Estimating[END_REF], Innovaya Visual Estimating [START_REF]Innovaya Innovaya Visual Estimating[END_REF], CostX [START_REF]Exactal CostX® | Exactal CostX : Construction Estimating Software | On-screen Takeoff Software[END_REF], and Nomitech [START_REF]Nomitech Nomitech Construction Oil & Gas BIM Cost Estimating Software, Estimating Services[END_REF], have been developed and applied in the construction cost estimation. However, based on case studies of the software using in cost estimation process, for instance BIM cases [START_REF] Skidmore | Merrill Standardizes Freedom Tower Project on Autodesk Revit Platform[END_REF][START_REF]Bentley Review and Study of the Opera Theater Interior and New Works[END_REF][START_REF]Graphisoft World's Tallest Residential Tower Designed with 3D Virtual Building Concept[END_REF][START_REF] Harty | Implementing building information modelling: a case study of the Barts and the London hospitals[END_REF], and quantity surveyor cases [START_REF] Matipa | How a quantity surveyor can ease cost management at the design stage using a building product model[END_REF][START_REF] Gee | THE INFLUENCE OF BUILDING INFORMATION MODELLING ON THE QUANTITY SURVEYING PROFESSION[END_REF][START_REF] Xu | High value information in quantity surveying organizations[END_REF][START_REF] Xu | Cost Estimation in Building Information Model[END_REF][START_REF] Sabol | Challenges in cost estimating with Building Information Modeling[END_REF][START_REF] Olatunji | Building Information Modeling and Quantity surveying Practice[END_REF][START_REF] Xu | BIM Environment : Quantity Surveyor ' s Information Lifecycle[END_REF], estimators still have to read and extract useful information from the model or manully rebuild a three dimentional model specific for cost estimation then conduct measuring by strictly complying with specifications such as SMM [START_REF]Quantities for Works Procurement[END_REF] or Professional Practice Guides [START_REF][END_REF] then applying unit price intuitively. Because of working complexity and comprehending deviation during the process, analytical cost estimation is both timeconsuming and error-prone [START_REF] Ma | Framework for Automatic Construction Cost Estimation Based on BIM and Ontology Technology[END_REF].

To improve the communication efficiency of BIM, Hartmann (2012) introduces semiotics to analyse BIM systems. This semiotic framework is focusing on technical perspective [START_REF] Andersen | A theory of computer semiotics: Semiotic approaches to construction and assessment of computer systems[END_REF], according to Liu (2000)'s semiotics ladder, it focuses on IT-platform, however, to author's best of knowledge, the communication problem is an inherent issue due to the nature of construction industry [START_REF] Eccles | The quasifirm in the construction industry[END_REF]. The analysis solo focuses on the technology part cannot solve the inherent problem of construction industry. High level requirements are not technical, but mainly social and organizational. Therefore, the success of information systems implementation depends more on how well an organization is prepared and organizational aspects are integrated rather than the pure technical systems itself [START_REF] Cui | Infrastructural Analysis for Enterprise Information Systems Implementation[END_REF].

Eastman [START_REF] Eastman | Building Product Models: Computer Environments, Supporting Design and Construction[END_REF] reveals that there are two major perspectives that influence the form of information technologies in the building information modelling: the organizational perspective, the technical perspectives, which includes software technology, the system architecture perspective, and the modelling technology perspective.

Organizational perspective depicts the structure of organization will influence information exchange and integration requirements. For example, traditional construction team, which is a virtual team with dispersed members working for a single project will have different requirements in contrast to an international building company that have various divisions, such as design, costing, and construction divisions [START_REF] Vanlande | IFC and building lifecycle management[END_REF]. Organizational requirements will guide the information techniques of the construction industry. Technical perspectives describe contribution from software technology, for instance new programming languages, function libraries, and exchange standard; the system architecture perspective, for instance different implementation methods, service oriented architecture (SOA) and P2P networks etc.; and the modelling technology perspective depict different modelling languages which focus on interoperability issues.

Current Ontology Application in BIM-based Cost Estimation

Based on our literature reviews, current BIM-based cost estimation is a fragmented process with knowledge. Along the cost estimation process, IFC model provides the information of a building, IDM verifies the information exchanged between IFC model and the cost estimation, says quantity take off [START_REF]buildingSMART alliance Draft QTO Information Delivery Manual[END_REF]. And the IFD supply the detailed components information contained in the general IFC model, however supports to cost estimation is not facilitated. Thus we need further improvement to BIMbased cost estimation.

Table 1. Comparison between estimation methods

Estimation method

General Cost Estimation Process Cost Item Quantification Unit Price Determine Conventional Cost Estimation

Manual Manual

BIM based Cost Estimation

Automatic* Automatic*

Ontology

Improved BIM and language used

1: Describe cost item comply with standard; IFCbased ontology. 2: Identify working condition to select cost item; OWL 3: Identify project location to select labour cost; UML+OWL. 4: Identify construction condition to adjust unit price; ontology language not specified Note: BIM based QTO and price identification doesn't comply with standard 1: [START_REF] Ma | Semi-automatic and specification-compliant cost estimation for tendering of building projects based on IFC data of design model[END_REF]; 2: [START_REF] Lee | BIM and ontology-based approach for building cost estimation[END_REF]; 3: [START_REF] Abanda | An ontology-driven housebuilding labour cost estimation in Cameroon[END_REF]; 4: [START_REF] Staub-French | A feature ontology to support construction cost estimating[END_REF] In table 1 these researches highlight that highlight the gap of BIM-based cost estimation which it doesn't satisfy the needs of domain users. The different ontology languages used concerns us, we argue that without a process for integrating knowledge of cost estimation, such kind of knowledge is still lost by the system and mainly maintained by individual cost expertise. Furthermore we also believe that the general process can be further breakdown to support professional activities in detail, for example describe, identify, select, and adjust etc. can be employed to describe professional cost estimation process. We believe that without a new stance to review cost estimation as a human intervention process and without a comprehensive framework to provide a foundation of interaction between IT platform and human function, professional works cannot be further improved.

The greatest challenge however is that of engaging in the development of knowledge representation in BIM-based model which is a knowledge representation language as well. This requires a fully "a cost estimator mind" with high software modelling knowledge that can model the processes of developing a cost estimation. Thus it represents two major problems that the complexity of knowledge language (industry foundation classes and ontology language) can hardly be understood by the domain user meanwhile knowledge engineer doesn't understand cost estimation in a good picture which could break cost estimation process into piece. Thus it is essential to have a knowledge capturing process could facilitate an integrated estimation process for estimating domain or at least could capture semantics and pragmatics.

Advantage of Applying Semiotics Framework to Cost Estimation

The adaption of the new approach needs a strong justification as it is essential for us to question about why stand from an organizational perspective for cost estimation.

Capturing the rationale and identifying the knowledge intensive processes is not a trivial task. It is difficult for experts to explain what it is that they know. To data, the only thing we know is that the expert in the quantity surveying organization needs to make assumptions about future cost resulting from: different locations, fluctuation of labour productivity and changes in the market conditions [START_REF] Tan | Best practice " cost estimation in land transport infrastructure projects[END_REF][START_REF] Sinclair | Construction cost data workbook[END_REF]. Corresponding to our two problems of cost estimation, which are quantification and pricing. In software, the main stream is quantification which start with building drawings. Firstly expertise will extracting a set of building elements from drawings, then decomposing them into cost items. Once these cost items are complied with standard, they often make comparisons and references to historical projects respectively in order to predict the cost of the new project [START_REF] Rush | Expert Judgement in Cost Estimating: Modelling the Reasoning Process[END_REF].

Together with the concerning of the development of information system, we adopt organizational semiotics which trying to understand cost estimation from an estimating process perspective. By capturing knowledge, the reasoning and inference steps can be delivered to the development of information system. We incorporate a suite of semiotics tools: semantic analysis and norm analysis [START_REF] Liu | Semiotics in Information Systems Engineering[END_REF]. Firstly, it identifies concepts of interest and the ontological dependency between semantic units, having established the ontology chart; it will then ascertain the semantic relations. Hence, for-malising these relationships to model the behaviour of organisational systems design [START_REF] Tan | A Semiotic approach to organisational modelling using norm analysis[END_REF]. In our research, the main focus addressed in engineering aspect has been put onto knowledge representation and information analysis to provide pragmatic and semantic support to quantification and pricing for cost estimation. This engineering perspective is related to information system engineering, which studies information system design and development. There are two major reasons why the engineering aspect is important to the automatic cost estimation:

 Adopting a proper information system engineering perspective helps grasping quickly the importance of information analysis and knowledge representation for cost estimation. The knowledge and information have to semantically represented, and reasoning engine can be supplied to enable estimator to leave tedious works as much as possible to system, in other words, to enable the system to automatic or semi-automatic perform cost estimation;  On the other hand, with the rapid development and heavy use of IT, cost estimation needs a technology-led updated estimating approach. This approach should incorporating human inference, and we argue that the analyst should use compatible and systematic analytical methods as used in information system engineering or the related disciplines. Gaining a clear understanding of the state-of-the-art approach to information system could nourish the ideas for up-to-date studies of cost estimation and receives the payoff from information system for cost estimation;  The semiotic approach takes one a step further. It will stress the distinctions as well as the interdependent links between the organization, the business process and the IT system. The notion of human responsibility and possibility of delegation of functions to an IT system is clarified.

Therefore, the authors' approach to 'expertise-based' cost estimating, is first to examine the current practice via a well-established framework, which links the physical world and social world through the information mechanisms expertise use in the organization. Secondly we employ semantic analysis in order to understand and capture the procedure knowledge used by experts when perform surveying, moreover standard investigation and observation have been conducted. By understanding these issues, it becomes possible to model the expert behaviour and further developing model in the sense of computability. Furthermore integrating such knowledge in a BIM system which enabling a knowledge-based approach to professional services. It is interesting to notice that some researchers are tagging IFC model as a semantic rich model [START_REF] Grzybek | Inclusion of Temporal Databases with Industry Foundation Classes-A Basis for Adaptable Intelligent Buildings[END_REF][START_REF] Nicolle | Semantic Building Information Model and multimedia for facility management[END_REF][START_REF] Steel | Model interoperability in building information modelling[END_REF], but others are claiming that IFC has insufficient semantic contained in the entity and relationships [START_REF] Shen | Semantic 3D CAD and Its Applications in Construction Industry -An Outlook of Construction Data Visualization[END_REF][START_REF] Venugopal | Formal specification of industry foundation class concepts using engineering ontologies[END_REF][START_REF] Venugopal | Formal Specification of the IFC Concept Structure for Precast Model Exchanges[END_REF]. This conflict has been addressed by our framework.

Pilot Study and Results Discussion

An investigation of BIM-based cost estimation through organizational semiotics ladders has been conducted, from the physical token to social norms, six aspects of signs in the semiotics ladder of IFC-based cost estimation summarized the findings in the analysis, due to page constraints, and detailed results are not presented in this paper. At technical perspective, in the physical level, STEP file and API usage is sufficient for establishing software integration and database exchange, however there is no im-plementation in knowledge base. In the empirical level, the emphasize is focused on IDM, which provides a mechanism to reduce the information uncertainty, however it is still highly in the initial phase and did not address the semantic, pragmatic and social problem derived from organizations. In the syntactic level, IFC provides a powerful schema that transmit construction information for all stakeholders but the redundancy and complexity of schema is barrier for the implementation. Moreover, regarding the domain practice, in other words the professional service provided by the participants, is requiring new entities that should be defined in the schema, especially the standards and professional activities.

IFC lacks the formal specifications to relate the entities and relationships to reasoning mechanisms from the human reasoning process perspective. As we discussed previously without an integrated process of cost estimation and a systematic framework, in the semantic and pragmatic level, the pattern of behaviour is not fully recognized and defined. For instance, in the current detailed cost estimation process, Comply with standard is a description of this behaviour, but the activities are not recognized nor computer supported. Other examples like forming behaviour which should before adjust behaviour has not been recognized either. These unrecognized behaviour patterns on the one hand are providing the flexibilities to do cost estimation but also is a time consuming process for cost estimation as expertise are mostly dealing with various software packages and attempting to link all these behaviours together to deliver cost estimation via quantity surveying approach.

After producing ontology chart of QS organization, the above three ladders, which are semantic, pragmatic and social, can be covered from an organizational perspective. Semantic analysis reveals professional activities that expertise are acting to accomplish their tasks. Norm analysis shows the pattern of expert problem solving and the logic behind the process. Briefly, professional activities and norms can be defined in the semantic. The affordances revealed in the semantic analysis can be formed as information requirements in empirical level. In figure 2, due to page limitation, we represent the stage of preparation (it can also be called classifcation stage), there are four actions we need to focus. They are dissemble, decompose, selects and synthesis. Figure 2 represents the semantic units translated into semantic web ontology (OWL), which is a knowledge representation language. The language has been widely accepted and used in the construction domain. All the categories can be related with professional activities, e.g. quantity surveying in the object property. It is important to notice that the most important aspect of OWL is their emphasis on tractability of inference. Furthermore a problem instance is solved by describing it and then asking if it is subsumed by one of several possible solution categories. By revealing professional activities and showing the dependency between semantic units as well as employ a special purpose reasoning engine, for example rule-based reasoning in logic programming, we could get a step further to implement the knowledge-based system, see figure 3. Prepare stage: According to [START_REF]The Royal Institution of Chartered Surveyors RICS New Rules of Measurement -Order of Cost Estimating and Elemental Cost Planning[END_REF], the estimators first receive the order of cost estimation request from client. And the estimators will receive information about the new project in various forms. They receive a request to do the work, and data such as 3D models, drawings and project documents. From this information, the estimator deepens their understanding of what it is that needs to be estimated by synthesising all the data and information. The estimator needs to analyse the requirements, decompose the project and classify the type of product. A Work Breakdown Structure (WBS) is employed and used as the framework to cost the new product [START_REF]Quantities for Works Procurement[END_REF]. During the decomposing of project, the expert may need to obtain more data to clarify the product of the project. They also need to understand the constraints in terms of time and resources. Once they understand what is required, they establish and document any ground rules and assumptions and identify the main cost drivers of the project. 2 discusses select in detail for an illustration. Norm analysis specify the rules used during the process, which has been illustrated in the logic programming language, see figure 4, when expert perform professional activity of select units in order to measure wall1 and wall2, the condition has been specified according to the standard and successfully differentiate two units for two walls. It presents feasibility of realizing quantity surveying in a logic programming environment. Expertise strict applies measurement rules, the process can be depicted like that whenever certain condition meets, a particular measured unit will be selected, and the same as construction product, and construction work results.

measured unit

Example: 1. Masonry, width of damp-proof is 500mm 2. Potential measured units: length in meter, area in square meter.

Together with the building section 14: Masonry, if the width of damp-proof is larger than 300mm, then it should be measured in square meter Measured unit: square meter Knowledge: Memory of the conditions for example 500mm width.

Conclusion and Future Research

In a summary, IFC is a powerful modelling language and is viewed as a semantic rich data model. More specific, it presents the project components and it's constructing processes, and how they related to each other, especially for its geometry representation. However semantic contained in the IFC is mainly focused on the components and constructing process information. Regarding the new framework introduced to BIM-based cost estimation, IFC lacks of semantic, pragmatic and social from a human reasoning perspective in which there are two aspects of knowledge, they are 'know-what' (could be mostly stored in the IFC) and 'know-how'. As we can see the domain knowledge which in terms of norms is generally manipulating the compo- Organizational semiotics has the capacity to reveal full semantic units for expert reasoning process and provide the alignment between semantic and pragmatic. The semantic units are modelled by organizational semiotics ontological chart, the ontological dependency fully describes the organization structures, inputs (semantic), professional activities (pragmatics), and results (intended semantics). By a simple mapping between OS semantic model and OWL semantic model, the revealed semantic units can be converted to OWL ontology in order to establish a common vocabulary of quantity surveying under a BIM environment.

This research highlights the importance of alignment between semantic (domain ontology) and pragmatic (meaning in use), it contributes also to identify a new approach of knowledge engineering for construction professional services under BIM environment. The roadmap and government report of BIM development confirm that BIM is toward a centre database of construction project. We believe that an integrated approach of semantic and pragmatic could promote BIM into a knowledge-based system, which currently hasn't been realized. Therefore the benefits can be identified from several perspectives, which are industry, domain user and research. From an industry perspective, a knowledge-based system which not only store descriptive knowledge but also procedure knowledge is essential for industry development. From a domain user perspective, implementing new techniques should truly benefits to the domain in terms of efficiency and effectiveness that aligned with human reasoning process. From a research perspective, semantic information exchange is the main stream of researches however the leverage of ontology implementation is still at the first stage which is the classification reasoning. Introduced new approach of knowledge engineering could facilitate discussions on the suitableness of general knowledge engineer process in the BIM environment and implementing the ontology in an innovative approach.

However the limitations are that revealed semantic units of organizational units and agents have not been used and there is no explicit contribution to pragmatic and semantic consistency although they are extreme important to the structure of BIM environment. On the other hand, virtualisation of this representation for domain user is quite difficult as there are many concepts and relations integrated and result in a human unreadable diagram. Future research will be focusing on find all the instances for the semantic units based on a case study, virtualisation of ontology need also being investigated that could be easily understood by domain user and redundancy of semantic units could be reduced in order to provide a precise semantic model of BIMbased cost estimation.

Fig. 1 .

 1 Fig. 1. Ontology Chart: Preparation of cost item

Fig. 3 .

 3 Fig. 3. Semantic and Pragmatic Implementation MapTable2discusses select in detail for an illustration. Norm analysis specify the rules used during the process, which has been illustrated in the logic programming language, see figure4, when expert perform professional activity of select units in order to measure wall1 and wall2, the condition has been specified according to the standard and successfully differentiate two units for two walls. It presents feasibility of realizing quantity surveying in a logic programming environment.

Fig. 2 .

 2 Fig. 2. Knowledge Representation of Analytical Cost Estimation in BIM

Fig. 4 .

 4 Fig. 4. Results from a Logical Programming Environment

Table 2 .

 2 Semantic Unit Analysis: select

	Semantic Unit: selects
	Input:	Action description:	Output:
	Conditions;
	Potential measured units


Luo Aimin

Xueshan

Shu Zhen

Luo Xueshan

An Evolution Method of Service View Products Supported Dynamic Integration of Information Resources

Keywords: Architecture, Operational activity, Service View, System Resource, Evolution, Dynamic Integration

des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

Introduction

Information system architecture is defined as the structure of components consisting of its system, relationships, and the disciplines and guidelines governing their design and evolution over time [1-3]. It has great importance on the information system design, development, operation and evolution. Architecture is one of the key technologies to guide the information system integration. At present, much research on information system architecture is generally conducted based on the research of DoDAF. The original information system architecture Framework (C4ISRAF, DoDAF, i.e.) is based on many views, such as "Operational View, System View, Technical View," etc. through the mapping between operational activities and system functions, provides an integration mechanism of information system resources to support a specific operational mission, while it is difficult to describe and analyze the dynamic integration process of information system resources to support the dynamic adjustment of operational mission in the future complex, changeable environment. Although DoDAF2.0, NATOAFv3.0, MoDAF1.2 and other latest architecture frameworks including the description of service view [4-6], they just only describe the definition, role and content of the service view products without analyzing the internal logical relationship between operational view, system view and service view, so that it is difficult to guide modeling and analyzing application of the service view products. Therefore, using the SOA and service-oriented thinking [START_REF] Chen | Towards Service Engineering: Service Orientation and Business-IT Alignment[END_REF][START_REF]Software as a Service (SaaS): An Enterprise Perspective[END_REF] , this paper extends the original information system architecture framework with increasing the service view products description in order to achieve the separation between the operational activities and the system resources. Then under the service view framework, this paper presents the modeling method of the service view products, and focus on the evolution method of service view products to support the dynamic integration process of the information system resources. This paper is organized as follows. In section 2, we present a service view description framework of information system architecture. Section 3 discusses modeling methods of the service view products within information system architecture. In section 4, we propose an evolution method of service view products within information system architecture. Section 5 concludes the paper by noting the future works.

A Service View Description Framework of Information System Architecture

The Original Information System Architecture Framework and Data Elements Relationship

The original information system architecture framework mainly described the system from three perspectives: the operational requirement and application, system design and technical constraints, namely Operational View, System View and Technical View [START_REF]C4ISR Architecture Framework Version 2[END_REF][START_REF]DoD Architecture Framework Version 1.0 Volume I: Definitions and Guidelines[END_REF][START_REF]DoD Architecture Framework Version 1.5 Volume I: Definitions and Guidelines[END_REF] . In particular, operational view describes the operational mission decomposition, operational activity model, operational process model, the rules of operational activities execution and information exchange etc. which is contributed to complete the operational mission. Through the traceability relationship between operational activities and system functions, it can determine the relationships of systems, system functions, system communication and data transmission to support to complete operational activities, and provides an integration mechanism of information system resources. The structure and data elements of the original information system framework are shown in figure 1.

System Node

System View Operational View

Technical View

Fig. 1. The structure and data elements of the original information system architecture.

The Reason of Introducing Service View

Under the guidance of the original information system architecture, to complete the system mission and realize the dynamic integration of system resources, the data elements of operational view and system view has following relation: the operational mission can be described by operational nodes which decomposed from operational task, operational activities and the relation between operational activities. The operational activities execution process need to produce and consume operational information, and operational nodes use system resources, operational activities are automated by system functions, system data exchange is fulfilled by operational information exchange between operational activities. Specifically, it is shown in the figure 2.

Source

Use

System resource may quit

Performes Performes Create Read

Operational activity process oriented system resource integration Fig. 2. Operational activity process oriented system resource integration However there are many problems located in this system resource integration mechanism to complete operational activities process: firstly, system resources integration is difficult, such as the system A and B located in figure 2, may be developed by different developers using different platforms, different language and different technical implementation. Although the design of architecture describes the interface and data exchange standard of two systems in order to support the operational activities process, the workload of system integration is still relatively large. Secondly, under the condition of operational requirement change, the operational activities process may also change, system resources maybe quit or fail, and a new system resource need to be added the operational activities execution process. These changes need system resources described in system view adjust their structural connection according to the change of operational requirement and the state of system resources, in order to adapt to the change of the operational activities process and system resources. However the heterogeneity among system resources makes it is difficult to support the system resources structural connection rapidly change.

Cope with the above demand, using the SOA and service-oriented thinking, this paper brings forward a service view, between operation view and system view, to describe services, manage services and the interaction process between services from the per-spective of service-oriented. The services can support the exchange of information between operational activities through XML data of standard SOAP protocol.

A Service View Description Framework of Information System Architecture

Service view acted as the intermediate layer between operation view and system view.

On the one hand, it can abstract and package the distributed, heterogeneous and interconnection system resources of system view, on the other hand, it also need to support and adapt to the change of operational activities process in operational view. Therefore, the data elements described in service view include the description of service itself, such as service structure, service interface, service behavior, service property, etc. and the relationship between services, such as service connection structure, service interaction rules, service level, etc. Therefore the service view description framework can be divided into: the description of service itself, the description of relationship between services and the description of the relationship between and the relation between services and other architectural elements, as shown in the figure 3. In order to avoid confused with the product name of systems View (SV), the name of Service View taken from the Service Oriented View, referred to as SOV.

3 The modeling and description method of service view products within information system architecture

The modeling and description method of each service view product

(1) Service Description (SOV-1) This product is the foundation of the description of other service view products. This product mainly realizes the package and description of a single system resources, namely the description of member service. Member Services(MS) can be represented by the following nine-tuple:

( , , , , Pr , , , , ) MS ID Name Description Operation ovider Input Output Capability QoS  Among them, ID represent service identification, Name represent service name, Description represent the description of service function or the supported operational activity,

Operation represent the operation provided by service, Pr ovider represent the service provider's information,

Input and

Output respectively represent the input and output parameters of the service, Capability represent the service ability, QoS represent the service quality attributes.

(2) Service Taxonomy (SOV-2) This product is mainly responsible for the classification and management of numerous member services involved in the information system, including hierarchical relationships, combination relations, derived relations and classification relations of member services. For this product, we can use the concept of the Service Group, to distinguish services from the similarity of service function. Service Group (SG) can be represented by the following seven-tuple:

( , , , , , , ) SG ID Name Description Operation Input Output Capability 
The meaning of each element in this tuple is similar to the element in MS . Each service in the SG is corresponding to one member service. Any service in the same SG has the same function and interface, but the service provider's information and QoS are different.

(3) Service interaction process model (SOV-3) This product is mainly used to describe the dynamic interaction between services, to support to complete operational activities process. We can use object-oriented Petri net to model this product [START_REF] Shu | Research on Military Information Service Composition and Validation Method Based on Object Petri Net[END_REF] . Using the advantage of expression ability based on object-oriented Petri net, we can solve the defects of enough semantic expression based on ordinary Petri net. We can use the object of object-oriented Petri net to describe the sub-processes, and use the object Petri net hierarchical description mechanism reduces the complexity of modeling service interaction process, and can establish a mapping between service node and service group through elements of object-oriented Petri net, such as token, action function and predicate transfer function, etc. in order to solve the path selection of uncertainty activity and system resources dynamic change problem in the execution process of service interaction, to meet the needs of service interaction process model description.

(4) Mapping between service and operational activity (SOV-4)

This product is mainly used to describe the traceability relationships between operational view and service view in system architecture design, to ensure the accessibility between operational activities and services supported operational activities. It is a many-to-many relationship between services and operational activities. The traceability matrix can be used to describe this product. Traceability matrix can be represented by the following six tuple: (5) Mapping between service and system resource (SOV-5) This product describes the traceability relationships between services and system resources, to ensure services can be implemented and deployed by the specific system resources. It is a many-to-many relationship between services and system resources. The traceability matrix can also be used to describe this product. Traceability matrix can be represented by the following six tuple:

( , Re , , ,
( , Re , , , , ) SerToSys ID lDescription SerID SerName SysID SysName 
The meaning of each element in this tuple is similar to the element in SerToAct .

The relationship between service view products

According to the above analysis of description and modeling method of service view products, the logical relationship between service view products is shown as figure 4. Among them, SOV-1 implement system resources packaged modeling and description, and set the detailed description of member service. With using the concept of service group, SOV-2 can realize classification management of member services described in SOV-1. Mapping relationship between services and operational activities (SOV-4) and mapping relationship between services and system resources (SOV-5) determine the traceability mapping relationship among service view, operational view and system view, and with other products of service view can realize the separation between system resources and operational activities. system architecture

In current complex, changeable environment, operational mission and state of system resources are easy to change, which requires decision makers adjust operational activities process and system resources timely according to the actual situation [START_REF]Business Alignment and Agility[END_REF] . Because the heterogeneity of information system resources, it is difficult to adjust system resources to adapt to the adjustment of operational activities process. Therefore, in the information system architecture design level, describing and analyzing the possible evolution requirements of system execution process is convenient to guide information system executing to adapt to the change of information system construction demand in the future.

Evolution demand of information system architecture

(1) system resource failure As in figure 5, through the analysis of the operational mission requirements, operational activities process model is established, including operational activity A, B, C and the information exchange among them. According to the mapping relationship between operational activities and system resources, operational activity A, B, C respectively supported by system resource 1, 2, 3, the demand of information exchange among operational activities determines connection relationship among system 1, 2, 3. Use system2' replace system2 Need built connection between system 2' and system 1,3

New increasing system Need built connection between system 4 and system 1,2',3 Fig. 5. Evolution demand of information system architecture Assumes that system 2 suddenly becomes invalid, it is difficult to support to complete operational activity B. Then you need to use a system 2' which has the same function as system 2 to replace system 2, to enable the operational activities process to continue. Owing to the heterogeneity between the system resources, system 2 and system 2' may be developed by different manufacturers, used different techniques to realize, which cause their interfaces are different and difficult to establish communication connection between system 2' and system 1(system 3), thus leading to the failure of the operational activity execution process, affecting the completion of operational mission.

(2) Operational activities process adjustment Using the above example shown in figure 5, assume it is need to increase new operational activity D, at the same time the logic relations between activity D and original activity A, B, C, such as exchange of information and sequential process, are set up. In order to satisfy the adjustment of operational activities process, it need to increase system 4 in system resources, and need to increase information exchange relations between system 4 and original system 1, 2', 3 according to information exchange relations of operational activity D. Also, owing to the heterogeneity between the system resources, it is difficult to establish communication connection between system 4 and original systems in order to support or adapt to the adjustment of operational activities process quickly.

The analysis of service view products evolution process

Service view acted as the intermediate layer between operational view and system view can effectively realize the separation between operational activities and system resources, and do not need specify a specific service in the service interaction process model, in order to effectively adapt to the evolution requirement of system resources failure and adjustment of operational activities process.

(1) The evolution process of service view products under system resource failure In service view, the execution resource in service interaction process model(SOV-3) choose service group, not specify the specific member service instance. Therefore we can use service group to deal with the failure situation of system resources. Service view products evolution process is shown in figure 6, assume that the failure system resource is the specific member service instance chosen in service interaction process model.

Step 1: Collect and manage member services information using service group, and learn member service status and function change through perception context and environment monitoring.

Step 2: When the service group learn the member service served as execution resource in the service interaction process model is difficult to meet the needs of the service interaction process execution, Service group reselect another member service served as the new execution resource in the service interaction process model, which does not affect the execution of service interaction process and does not need to adjust operational activity process.

Step 3: When all member services in service group are difficult to meet the functional requirements of service interaction process execution, we can choose other backup service group registered in SOV-2, and choose the suitable member service instance meeting the requirement of service interaction process execution through backup service group. If not find alternative service group, then turn to the fourth step.

Step 4: Reselect redundant service interaction process model registered in SOV-3, and need to pay attention to ensure the mapping effectiveness between service node and service group.

Step 5: If there still exist service group failure mapped by service node in redundant service interaction process model, it need to perform evolution operation on service interaction process model by architecture designers.

SOV-3

The execution service group

Service logic process level

SOV-4

The adjustment of operational activity process (2) The evolution process of service view products under operational activities process adjustment As operational activities execution process is supported by the service interaction process, it is need to analyze and adjust the service evolution process to deal with operational activities process adjustment.

Step 1: In the view of future uncertain operational activities process, we design the redundant service interaction process in SOV-3. If the redundant service interaction process model can satisfy the operational activities adjustment, the evolution process is over, otherwise turn to the second step.

Step 2:, According to the adjustment of operational activity process, architecture designers perform evolution operation on original service interaction process model to ensure the new model can support and adapt to the adjustment of operational activities process.

Note that, the above two evolution processes are likely to be involved in the evolution of service interaction process model. The evolution refers to adjust the service interaction process according to the adjustment of operational activity process, to support or adapt to operational activities after the adjustment process. From 3.1, we know service interaction process model is described by object-orient Petri net model, therefore the evolution of the service interaction process model can be converted into the opera-tion of increase, delete, replace in object-orient Petri net model, at the same time also need to ensure the structure correctness and service resource effectiveness of service interaction process model after revolution. Due to the limitation of space, the specific algorithm is not introduced, and it can be found in [11].

Conclusions

This paper presents the modeling and analyzing of the service view within the information system architecture using service-oriented thinking and research on SOA, in order to describe and analysis the system resources dynamic integration and evolution demand of information system in the future complex, changeable environment. Our contributions make a base ground for the future research of information system architecture designing and analyzing. Future work will be perfect service view description framework of information system architecture and develop modeling tool based on this theory.

Fig. 3 .

 3 Fig. 3. The service view description framework of information system architecture

Fig. 4 .

 4 Fig. 4. The relationship between service view products

Fig. 6 .

 6 Fig. 6. The evolution process of service view products

Use Is automated by Is fullfilled Is automated by

		Source Node	Operational Activity Process	Destination Node
		Operational Activity	Produce	Element Information	Consume	Activity Operational Sink
	System resource
	System A may fail	System Function-a		Data Exchanges		System Function-b	System B System resource may fail
	System C
	New resource may
	join


John Krogstie
email: krogstie@idi.ntnu.no

Shang Gao
email: shanggao@idi.ntnu.no

Yuhao Yang

The Adoption of Smartphones Among Older Adults in China

Keywords: Adoption of smartphones, UTAUT, older adults

des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

Introduction

Today, smartphones become increasingly important in people's daily life. A smart phone is a mobile phone with more advanced computing capability and connectivity than basic feature phones. It allows users to make video calls, download and transfer files, and use internet-based applications. Smartphones have the potential to enhance the quality of people's life [START_REF] Gao | Lifestyles and Mobile Services Adoption in China[END_REF][START_REF] Gao | Adoption of mobile information services: An empirical study[END_REF]. For instance, people can get immediate access to information on a variety of topics through their smartphones. People get opportunities for entertainment in the form of games, movies, books through their smartphones. Moreover, smartphones can facilitate communication among family, friends and colleagues via social networking tools, emails, etc. Most countries in the world are experiencing an increase in the average age of their population. The ageing of the population is one of the major challenges most countries have to face over the next few decades [START_REF] Peacock | Senior citizens and Internet technology[END_REF]. Older adults face challenges when they are using smartphones. A gap seems to exist in the adoption and use of smartphones by older adults. Some typical issues that impact their use of smartphones are as follows, lack of skills, too expensive phones, security and privacy concerns. Given all the potential benefits smartphones can bring to the daily life of older adults, there is still an urgent need to examine the means to enable older adults to use smartphones. This research intends to bridge the research gap in the adoption of smartphones among older adults in China. The objective of this research is to examine the adoption and usage of smartphones with older adults in China. We attempt to investigate how various factors impact older adults' intention to use smartphones in China by a research model based on previous technology diffusion theories. The term older adult has been defined in a variety of ways in different articles, which ranges from over 40 to over 75. The distinction of "older" depends upon the specific context under consideration. Most people over 60 lack the essential skills to perform user survey and computer literacy to use smartphones because their education was interrupted during the Cultural Revolution in China. If we defined the older adult as people over 60, it would be extremely difficult to collect survey data for this research. Therefore, we defined older adult as people over the age of 45 in this study. The rest of this paper is organized as follows: Section 2 discusses the theoretical background of this study. The research model and hypotheses are presented in Section 3. The research method and results are described in Section 4. This is followed by a discussion of the findings in Section 5. Section 6 concludes this research.

Background

Benefits of use of smartphones for older adults

Older adults can benefit from the use of smartphones in a number of ways. Mobile services available on smartphones may help older adults enhance communication with their families and friends, enrich their personal interests, and check various healthcare related information. Further, to address the problems raised by ageing population, many countries started Smart Cities project to fulfill older adults' needs across areas such as housing, social participations health care, and community support services, leisure, to make the city environment more elderly friendly. Smartphones can provide personalized health care, social services for older adults. Although there are many mobile services available on smartphones, many older adults are less aware of those services. This could be a potential reason why older adults do not use smartphones.

Digital Divide

Scholarly research on the digital divide has a long history back to the 1990s. Most researchers in Information Systems in the last two decades focus on Internet penetration through the lens of technology diffusion theory (e.g., TAM [START_REF] Davis | Perceived usefulness, perceived ease of use and user acceptance of information technology[END_REF], IDT [START_REF] Rogers | The diffusion of innovations[END_REF] , UTAUT [START_REF] Venkatesh | User Acceptance of Information Technology: Toward a Unified View[END_REF]). The digital divide refers to the gap between those who do and those who do not have access to new forms of information technology [START_REF] Van Dijk | Digital divide research, achievements and shortcomings[END_REF]. Research on digital divide often starts by looking at users' access to new technologies. The types of access can be defined as 'physical access' and 'beyond access'. An increasing number of researchers suggested to study 'beyond access' with additional attention to social, psychological and cultural background. For example, Van Dijk [START_REF] Van Dijk | Digital divide research, achievements and shortcomings[END_REF] found a shifted research attention on digital divide from physical access to skills and usage. Along with the popularity of computers and digital technologies, the digital divide in terms of physical access seems to be reduced in most developed countries. The uneven spread of the mobile applications on smartphones has contributed to the popularity of the concept of the 'digital divide' associated with smartphones. It highlights the emerging social gap between those individuals who use mobile applications on smartphones and those who do not. It is believed that the major gap is based on socio-demographic dimensions (e.g., age, region, income, educational background). To reduce digital inequalities, we must understand the reasons for non-users' resistance to the use of smartphones. Investigating this digital inequality is of help to understand the diffusion of smartphones with different ageing populations.

The adoption of smartphones with older adults

Research work has been carried out by researchers in studying various aspects related to the adoption of smartphones [START_REF] Gao | Developing an Instrument to Measure the Adoption of Mobile Services[END_REF]. In [START_REF] Chen | The acceptance and diffusion of the innovative smart phone use: A case study of a delivery service company in logistics[END_REF], Chen, et al. combined TAM and innovation diffusion theory (IDT) to study and explain the adoption of smartphones in logistics. Self-efficacy was a strong predictor of behavioral intention through attitude. Based on a study on the performance of mobile applications, Huang et al. [START_REF] Huang | Anatomizing application performance differences on smartphones[END_REF] indicated that smartphones could become a suitable substitute of traditional computer. But, the performance of the applications on smartphones is poorly understood. Although significant effort has been done to explore the adoption of smartphones, the research on the adoption of smartphones with older adults is still in its infancy. The samples used in previous research on the adoption of smartphones are relatively young. Concerning the research on the adoption of new technologies by older adults, most previous research [START_REF] Wagner | Computer use by older adults: A multidisciplinary review[END_REF] tends to focus on the use intention and adoption of computers and Internet by older adults. Lee et al. [START_REF] Lee | Age differences in constraints encountered by seniors in their use of computers and the internet[END_REF] examined older computer users' constraints at various age stages. An examination of the current literature reveals that few studies have addressed the use and adoption of smartphones by older adults. Pheeraphuttharangkoon [START_REF] Pheeraphuttharangkoon | Investigating the adoption and use of smartphones in the UK: a silver-surfers perspective[END_REF] investigated the adoption and use of smartphones with older adults in the UK. However, the sample size with people over 50 years old is quite small in their study. To our best knowledge, we have not found any studies addressing the adoption of smartphones with older adults in China. The digital divide along the age dimension has become a major concern in China. In developed countries, Internet penetration is saturated and average education level is high, it is easier for users to use smartphones. However, the average education level is lower, especially for older adults in China. According to the annual report 2013 from China Internet Network Information Center, the percentage of smartphone users aged above 45 is significantly lower than the younger generation. Therefore, it is worth to carry out this research to better understand older adults' behavior intention to use smartphones in China.

A research model that identifies important factors that impact older adults' intention to use smartphones was developed in this research. The proposed research model (see Figure 1) is an extension of UTAUT [START_REF] Venkatesh | User Acceptance of Information Technology: Toward a Unified View[END_REF], with a consideration of observability and compatibility from IDT [START_REF] Rogers | The diffusion of innovations[END_REF], and perceived enjoyment [START_REF] Van Der Heijden | Factors influencing the usage of websites: the case of a generic portal in The Netherlands[END_REF] [17] and price value [START_REF] Venkatesh | Consumer acceptance and use of information technology: extending the unified theory of acceptance and use of technology[END_REF] from other technology diffusion theories. We have developed eight research hypotheses based on the research model. Each hypothesis as labeled in Figure 1 is elaborated below.

Hypotheses developed from UTAUT

Four key factors from UTAUT, Social Influence, Facilitating Conditions, Performance Expectancy and Effort Expectancy, were included in our research model. Social Influence is the extent to which consumers perceive that important others (e.g., family and friends) believe they should use a particular technology. Previous research also indicated that social influence is important for the adoption of smartphones [START_REF] Zhou | The effect of flow experience on mobile SNS users' loyalty[END_REF]. Facilitating Conditions refer to consumers' perceptions of the resources and support available to perform a behavior. Users need to have digital skills to use smartphones. Performance Expectancy is defined as the degree to which using a technology will provide benefits to consumers in performing certain activities. Smartphones are able to provide potential benefits (e.g., always connected, healthcare information) for users. Once users have recognized these benefits, they are likely to use and adopt smartphones. Effort Expectancy is the degree of ease associated with consumers' use of technology. Learning a new technology often takes time and effort, particularly with older adults. If using smartphones is considered as an easy and straightforward process, users are likely to adopt smartphones. Thus, we proposed the following four hypotheses.

H1: Social Influence (SI) has a positive influence on older adults' intention to use smartphones.

H2: Facilitating Conditions (FC) has a positive influence on older adults' intention to use smartphones.

H3: Performance Expectancy (PE) has a positive influence on older adults' intention to use smartphones.

H4: Effort Expectancy (EE) has a positive influence on older adults' intention to use smartphones. Hypotheses developed from IDT Rogers [START_REF] Rogers | The diffusion of innovations[END_REF] indicated that innovation that are perceived by individuals as having greater relative advantage, compatibility, trialability, and observability, and less complexity will be adopted more rapidly than other innovation. To further understand older adults' intention to use smartphones, two factors from IDT were included into our research model. As for the case of smartphones, Observability can be defined as the degree to which smartphones are visible to potential users. Compatibility can be seen as users' belief in the consistency of using smartphones with the way they live and work. Previous research also demonstrated that the importance of Observability and Compatibility to the adoption of new technologies (e.g., e-banking [START_REF] Kolodinsky | The adoption of electronic banking technologies by US consumers[END_REF]). Therefore, the following two hypotheses were proposed.

H5: Observability (OBS) has a positive influence on older adults' intention to use smartphones. H6: Compatibility (COM) has a positive influence on older adults' intention to use smartphones.

Perceived Enjoyment and Price Value

Perceived Enjoyment is defined as the extent to which the activity of using a specific system is perceived to be enjoyable in its own right, aside from any performance consequences resulting from system use [START_REF] Van Der Heijden | Factors influencing the usage of websites: the case of a generic portal in The Netherlands[END_REF] [START_REF] Venkatesh | TAM 3: Advancing the technology acceptance model with a focus on interventions[END_REF]. Users can have fun when they are playing games, and playing music on smartphones.

Price value is another significant factor affects users' adoption of a new technology. Price value can be defined as consumers' cognitive tradeoff between the perceived benefit of the applications and the monetary cost for using them [START_REF] Venkatesh | Consumer acceptance and use of information technology: extending the unified theory of acceptance and use of technology[END_REF]. It is believed that users are likely to adopt smartphones when the benefits of using smartphones are perceived to be greater than the monetary cost of smartphones. Hence, we proposed the following hypotheses.

H7: Perceived Enjoyment (PEJ) has a positive influence on older adults' intention to use smartphones.

H8: Price Value (PV) has a positive influence on older adults' intention to use smartphones.

An Empirical Study with the Research Model

To understand older adults' use and adoption of smartphones in China, the proposed research model and hypotheses were empirically tested using the structural equation modeling approach.

Instrument Development

The validated instrument measures from previous research were used as the foundation to create the instrument for this study. In order to ensure that the instrument better fit this empirical study, some minor words changes were made to ensure easy interpretation and comprehension of the questions. For instance, wording was modified to fit the context of use of smartphones in China. A questionnaire was developed first in English and then translated into Chinese. Back-translation was conducted by bilingual third party to improve the translation accuracy. As a result, the measurement questionnaire consisted of 25 items 1 . A seven point Likert scale was used to examine participants' responses to all items in this part.

Samples

The data for this study were collected through self-administered questionnaires in the central part of China. The survey was distributed in terms of paper-based questionnaires individually from Aug 20th 2014 to Sep 30th, 2014. 132 completed questionnaires were collected, among which 121 of them were valid questionnaires (i.e., valid respondent rate 91.7%). Among the participants, 72 of the participants were male, and 49 were female. Moreover, 79.3% of participants had full-time jobs, 10.8% of participates had part-time jobs, 9.8% of participants had retired. Further, the top three most used featured on smartphones for the participants were: making phone calls, text messaging, and instant messaging feature (e.g., QQ, Wechat).

Measurement Model

The quality of the measurement model is determined by [START_REF] Bagozzi | The role of measurement in theory construction and hypothesis testing: toward a holistic model[END_REF]. Content validity, [START_REF] Bagozzi | Specification, evaluation, and interpretation of structural equation models[END_REF]. Construct reliability and (3). Discriminant validity [START_REF] Bagozzi | The role of measurement in theory construction and hypothesis testing: toward a holistic model[END_REF]. To ensure the content validity of our constructs, a pre-test of the questionnaire with a small group of respondents was conducted before the survey was distributed. To further test the reliability and validity of each construct in the research model, the Internal Consistency of Reliability (ICR) of each construct was tested with Cronbach's Alpha coefficient. As a result, the Cronbach's Alpha values range from 0.83 to 0.93. A score of 0.7 is marked as an acceptable reliability coefficient for Cronbach's Alpha. All the constructs were above 0.70. Convergent validity was assessed through composite reliability (CR) and the average variance extracted (AVE). Bagozzi and Yi [START_REF] Bagozzi | Specification, evaluation, and interpretation of structural equation models[END_REF] proposed the following three measurement criteria: factor loadings for all items should exceed 0.5, the CR should exceed 0.7, and the AVE of each construct should exceed 0.5. As shown in Table 1, all constructs were in acceptable ranges. The measurements of discriminant validity were presented in Table 2. According to the results, the variances extracted by the constructs were more than the squared correlations among variables. The fact revealed that constructs were empirically distinct.

As good results for convergent validity and discriminant validity were achieved, the test result of the measurement model was good.

Table 2. Discriminant Validity

Note: Diagonals represent the average variance extracted, while the other matrix entries represent the squared correlations.

Structural Model and Hypotheses Testing

The structural model was tested using Amos 20.0. The results of the structural model are shown in Figure 2. The R 2 (R square) in Figure 2 denotes to coefficient of determination. It provides a measure of how well future outcomes are likely to be predicted by the model, the amount of variability of a given construct. In our analysis, the R 2 coefficient of determination is a statistical measure of how well the regression coefficients approximate the real data point. According to the result, 77% of the variance of behavior intention can be explained by the research model. The standardized path coefficients between constructs are presented, while the dotted lines stand for the non-significant paths. Table 3 presents the path coefficients, which are standardized regression coefficients. As a result, five (H1, H3, H5, H6, H7) of the proposed eight hypotheses were supported. The positive effects of perceived enjoyment on intention to use was quite strong, as indicated by the path coefficient of 0.85 (p<0.05). The other path coefficients of compatibility, observability, social influence, and performance expectation, to intention to use were statistically positively significant at p<0.05. But, there was no significant positive impact of facilitating conditions, effort expectancy, and price value on the intention to use smartphones with older adults. Therefore, H2, H4, and H8 were rejected. Performance expectancy had a significant positive impact on older adults' intention to use smartphones, while effort expectancy did not have a strong positive influence on older adults' intention to use smartphones. It seemed that older adults did not use smartphones just because it was easy to use, but rather because they found it useful for their work and life. Therefore, smartphones providers need to develop better solutions to make smartphones more useful. This also implied that content providers of apps on smartphones have to pay more attention to the usefulness of the content available on smartphones for older adults. There was no significant positive impact of facilitating conditions on the intention to use smartphones with older adults. One possible reason was that facilitating conditions might be considered as a limiting factor when the needed facilitating conditions are not perceived by older adults. Therefore, the presence of the facilitating conditions did not motivate older adults to use smartphones. Another interesting finding was that price value had no significant positive impact on the intention to use smartphones with older adults. Since smartphones become inexpensive (e.g., the cheapest model from MI costs 100 USD) in China, most participants in this study can afford smartphones. It seems that they tend to focus on the factor (e.g., perceived enjoyments, performance expectancy) when using smartphones. Therefore, price value of smartphones becomes unimportant when it comes to the adoption of smartphones with older adults in China. However, we were also aware of some limitations. Firstly, we only tested the research model and research hypotheses with older adults from five provinces in the central part of China. This sample might not be fully representative of the entire older adults in China. Secondly, all the data were collected using self-reported scales in the research. This may lead to some caution because common method variance may account for some of the results that has been cited as one of the stronger criticisms of tests of theories with TAM and TAM-extended research [START_REF] Malhotra | Common method variance in IS research: A comparison of alternative approaches and a reanalysis of past research[END_REF]. However, our data analysis with convergent and discriminant validity does not support the presence of a strong common methods factor. Last but not least, the findings of this study may be limited due to the relatively small sample size.

Conclusion and Future Research

This research was designed to study the adoption of smartphones with older adults in China. To the best of our knowledge, we have not found any studies concerned with older adults' intention to use smartphones in China. This study investigated older adults' adoption of smartphones by extending UTAUT with a consideration of observability and compatibility from IDT, and perceived enjoyment and price value. A research model with eight research hypotheses was proposed in the study. Five research hypotheses were positively significantly supported, while three research hypotheses were rejected in this study.

Fig. 1 .

 1 Fig. 1. Research Model

Fig. 2 .

 2 Fig. 2. Results of structural modeling analysis

Table 1 .

 1 Factor loadings, composite reliability, and AVE for each construct

	Construct	Item	Factor Load-	Composite	AVE	Cronbach's
			ing	Reliability		Alpha
	SI	SI1	0.835	0.91	0.77	0.85
		SI2	0.947
		SI3	0.840
	FC	FC1	0.864	0.91	0.71	0.87
		FC2	0.790
		FC4	0.887
		FC4	0.835
	PE	PE1	0.860	0.90	0.75	0.83
		PE2	0.929
		PE3	0.804
	EE	EE1	0.941	0.95	0.87	0.93
		EE2	0.941
		EE3	0.917
	OBS	OBS1	0.939	0.94	0.89	0.87
		OBS2	0.946
	COM	COM1	0.941	0.95	0.87	0.92
		COM2	0.948
		COM3	0.905
	PEJ	PEJ1	0.937	0.94	0.89	0.87
		PEJ2	0.947
	PV	PV1	0.827	0.93	0.82	0.89
		PV2	0.945
		PV3	0.936
	IU	IU1	0.952	0.95	0.91	0.91
		IU2	0.960

Table 3 .

 3 Test of hypotheses based on path coefficient

	Hypothesis	Path	Hypothesis
		Coefficient	Result
	H1	0.10*	Supported
	H2	0.01	Rejected
	H3	0.25***	Supported
	H4	-0.14	Rejected
	H5	0.26***	Supported
	H6	0.33***	Supported
	H7	0.85***	Supported
	H8	-0.05	Rejected
		*p<0.05; **p <0.01; *** p <0.001
	5 Discussion
	In this research, we studied the adoption of smartphones with older adults in China.
	The most important determinant for users' intention to use smartphones was per-
	ceived enjoyment. If using smartphones is fun, older adults are more likely to accept

The survey items are available at this link: http://www.idi.ntnu.no/~shanggao/oldadults.html

Continuing with this stream of research, we plan to further examine the applicability of the research model with other group of users in China (e.g., people below 45 years old). Future research is also needed to empirically verify the research model with larger samples across the world. We also plan to carry out a comparative study with older adults in the developed countries.


Lily Sun
email: lily.sun@reading.ac.uk

Xian Jin

Qin Zheng
email: qing.zheng@mail.shufe.edu.cn

An Optimization of Collaborative Filtering Personalized Recommendation Algorithm Based on Time Context Information

Keywords: Personalized recommendation, collaborative filtering, time-context

établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

Introduction

Recommender algorithms belong to a class of personalized information filtering technologies that aim to identify which items in a catalog might be of interest to a particular user. The scenario is a very important factor for mobile e-commerce personalized recommendation process. User's interests and needs tend to change with time and space associated with situation changes. Therefore, how to accurately predict the information of interest to users has become a key issue in personalized recommendation problems. Traditional collaborative filtering algorithm does not consider the situation. Therefore, it cannot reflect the needs tendency of users due to the different situations. This shortage caused a lack of personality in recommendation process. The length of time will affect a user memory of interest degree, thereby affecting their user preferences. Meanwhile, the mobile commerce environment is dynamical, and the context information are facing constantly changing, thus affecting the user's interest and purchasing decisions.

Based on this, this paper research on the impaction from time contextual information to users interested and the user interest preferences attenuation occurs over time context information. This paper provides an UIT (users-project-time) model. The model can achieve precise recommendation and marketing mobile environments. Our research work contributes to three levels: 1) at the method level, we improve the traditional collaborative filtering algorithms, combined with the time context information and collaborative filtering algorithm and improved mobile environment recommended accuracy in traditional collaborative filtering algorithms; 2) at the theoretical level, this study intends to enrich personalized recommendation research of mobile commerce. Currently, most of the research is focused on mobile business mobile business process, trust, risk, and decision-making issue, but consumer behavior, personalized research is still at an exploratory stage. This study also improves the quality of the recommendation system by time context information; and 3) at the commercial value level, the development of mobile Internet and mobile commerce will enter a rapid growth phase, how to provide a valuable service for these users, and then find the right business model is an important strategy for many Internet companies. We provide also a reference model for personalized recommendation in mobile environment.

Theoretical background

Personalized recommendation algorithms

Collaborative filtering recommendation is the most successful technology. For example, Goldberg (1992) describes the similarity between users using artificial mail processing system. Ringo (1997) uses the social information filtering method and the music recommendation system.

Research on time context information recommendation

The traditional personalized recommendation only works with User-Item structure, it does not considerate the context information of user's. It cannot fully reflect the preferences of the user. For example, users like to browse news and information in "morning", like to browse social networks to share information in the "noon", like to play various entertainment games in the "night". Some users may order some things without payment online because of the exquisite pictures, but after whole day working, the users feels meaningless and then cancel the order. These user's preferences changes is due to the context information of user behavior changes. Schilit (1995) divides the context information into three categories, such as computing context, user context, and physical context. Chen (2000) considers that the time context information is another factor. Jonna (2005) divides the context information into five categories, i.e., physical environment, user goals, equipment application, link to person/service, and equipment connection. Kenta (2006) takes views of user's plan, time, user's friends, and external environment in a restaurant recommendation system. Zhang (2007) devises the context information in terms of user preference and context position, such context information refers to the ability to handle user terminal and wireless network. In a music recommendation system, [START_REF] Kim | Design of Ubiquitous Music Recommendation System[END_REF] sets the context information as gender, age, location, time, weather, temperature and pulse for a music recommendation system. Adomavicius and Tuzhilin (2008) put forward the definition of context information and the different method of the user model when context information is constructed. Other scholars (Wang et al., 2012) also offer some research in the theory, methods, and applications of context aware systems, e.g., the New York University, University of Konstanz, the IBM Institute, and the Microsoft research institute. In summary, the diverse context information is appropriately set according to the specific object of research. We select the context information based on the time dimension, and research the change of time context information under user's interest changes, and then improve the traditional collaborative filtering algorithm. With the development of mobile Internet, the research of context information, especially it has great theoretical and practical significance of the context information in mobile environment.

User preferences attenuation mechanism base on time

Data source and data collection

This research work adopts the movies rating dataset of Movielens provided by Minnesota University for our experiment on personalized recommendation. We selected the dataset of Movielens-100K, which contains 100,000 real rating scores for 1682 movies by 943 users. The data sparsity is 6.3%. This study adopts the accuracy of recommendation as the evaluation index in the other word, the ration of intersection of the TOP-N recommended list and predicting set relative to TOP-N recommended list is better when bigger. The item of predicting set is visited by the user in real world, as defined in Equation [START_REF] Abbar | Context-Aware recommender systems: A service-oriented approach[END_REF].

𝑝=|List∩Test|N (1)
where N is the count of TOP-N recommended list. N=30.

Improvement on time-base collaborative filtering algorithms

Time context information is introduced to improve the collaborative filtering algorithm on the time dimension. Our study takes the time weight function of users' interest attenuation and the time context weight of the user into consideration in the time to describe the impact on the users' preference, base on which the algorithm used to calculate the similarity between items in the collection can be improve. The following are details about how to decide the weight to improve the algorithm.

Improvement on time-based weight

Users' preferences decay over time.

f(u, t) = 1 1+𝛼|tui-𝑡uj| (2)
where 𝛼: decay parameter tui /tuj : behavior time of user u access the item i/j f (T) will be smaller when |tui-tuj| is bigger. The value of 𝛼 can be decided according to the change of system user interest. Lager value means big change since smaller value means small change. The interest degree of user u on item j in the original item based collaborative filtering algorithm is expressed in Equation ( 3).

(3) where Iu means the set of items accessed by user u j means the predicting item rui means the interest of user u on item i. rui will be 1 when the user u access the item i. After introducing the time decay function, the interest degree of user u on item i will change over time. K𝑗 means the neighbor items collection of item j. It can be calculated by Equation ( 4). ( 4) where t0 means the current time since tui means the time when user u accesses item i.

𝛼 can be decided according to the situation.

Improvement on resource-based weight

Because the users' early interest is similar with recent interest, this paper takes the similarity between items to measure the similarity between early and recent behavior. T means the recent time period of the user u. IuT is the set of the items accessed by user u in T. Iu means the whole set of the items accessed by user u. We got IuT⊆Iu. P(u,i) means the item-similarity-based weight since i∈Iu. The average similarity between item i∈Iu and the item j∈IuT can be calculated by Equation ( 5).

( 5) where | IuT | means the count of the items recent accessed in T. sim(i,j) means the similarity between item i and j, which can be calculated by Pearson correlation coefficient calculating formula: By measuring the similarity of the recent and early items accessed, we can figure out the influence on recent interest from the early interest. Sometimes, the interest is forgotten over time. But it can be evoked by the visual or other relevant stimuli, which will impact the users' recent behavior. The resource-based weight can improve the recommendation quality effectively.

Improvement on time-context-based information

The mobility of mobile device makes the contextual environment of the user changing dynamically. The interest and requirement will be different in the different contexture environment. For example, user will browser the news app after 18:00 on the metric and shop on line or play games at noon in the office and shop or have dinner outside at the weekend. So that introducing the time contextual information of the user into the recommendation system can help to figure out the users' interest and the weight of each interest. We take the users' time contextual information into consideration to calculate the similarity of the time to decide the users' interest, which provide the useful information for the recommended results. The vector model was used to express the set of time contextual information collected by n time contextual information. Given TCon-text= {TC1, TC2, …, TCn},in which TCi={tc1, tc2, …, tcn}, tci(1≤i≤n) is a time contextual information at time I and tci is an attribute of the information. This paper category the accesses time by week, and calculate the access preference everyday within a week. The time context information can be described as TC={Monday, Tuesday, Wednesday, Thursday, Friday, Saturday, Sunday}. Post to the time context information being defined, User-Time Matrix can be added into time division.

In the User-Time matrix, the task T as item I, the value of T is Ti, (i=0..6). The value in the matrix represents that user's interest degree in a day within a week. Base on this, we can get the time series similarity according to Pearson Correlation Coefficient.

Calculate user's interest preference base on items

This research work considers that user's interest preference changes based on time weight, item similar weight and time weight. Then the results can determine user preferences on items, judge the transfer direction of user interest more accurately and then provides a recommendation list more accurate for the users, improve the quality of recommendation system. Firstly the time context information was pre-filtered.

Secondly get the time context information similarity set N(t) was retrieved. Finally calculate time weight function and item similarity weight according to the N (t). In the time weight function Tuj∈N (t), items of similar time T∈ N (t), then u has access to items #i interest preference value user time context information as defined in Equation ( 6).

H (u,t,i) = 𝛼1×f(u,t) + 𝛼2×pt(u,i)

Results

The results of experiment

Through many times experiments, we obtain the best weight value combination recommendation accuracy rate is 0.2667, then transform the value of TOP-N, validate the recommendation accuracy under different N value. By adjusting the number of items in the list of recommended, determined recommendation accuracy under different N value, the results as shown in Figure 2. In our result, the recommendation accuracy is no less than 0.25 by improved collaborative filtering recommendation algorithm, even if N value changed in TOP-N recommended list, when N=10, the accuracy rate is the highest for the 0.3. This result is same as most of present e-commerce website recommenda-tion number. Thus, it is obviously shows that users have different preferences under different time context information.

Conclusion

Mobile commerce will change people's life. Accessing to the information users' needs in a short period of time become the key value. In this paper mainly results as follows: 1) Apply the time context information to the traditional collaborative filtering algorithms. Established the three dimensional matrix of user-item-time (U-I-T) by pre filtering function and combining the processing time context information; 2) Convert all times information to one day of a week, and then confirm the user's time interest, and then find the item which was accessed the second time at that time point, these results can improve the recommendation accuracy effectively; and 3) Combined the time function and item similarity. The arbitrary time in the interval time functions is the number of days within a week. This method reflects more clearly that user preference is influenced by time context information. On the other hand, combined with the recent information mining. It can determine the impact of the recent behavior of the current user's interests. The limitation of this paper is that the data source only can shows the visit behavior online. Therefore, the results of this paper needs more validation in actual scenario, such as mobile commerce. That is what I should improve in the future. And, I will continue to research in these problems: (1) accuracy and diversity of the recommendation algorithm. Currently, most of recommendation algorithms only consider recommending accuracy, while ignoring the diversity of the recommendation. But the user's interests are changeable. Therefore, it is lot of research work need to do on how to balance the two fetors the future balance is also a big problem. (2) The different explanation on different data sets. Different datasets shows different characteristics, the performance of various recommendation algorithms on these data sets will also have differences, the reason can be the further studied topics.

6

Fig. 1 .

 1 Fig. 1. Ebbinghaus forgetting curve

  𝛼i(i=1, 2)∈[0,1] shows the weight under different factors; ∑ 𝛼i = 1 𝑖 f(u,t) means that user #u interested in item #i attenuation degree with time and the time preference; p(u,i) is the weight based on items similarity; H(u,t,i)is user interest preference base on the time context information. The three functions characterize the time context information influence on the user's interests in different aspects, by adjusting the weight values of 𝛼 i to achieve more accurate recommendations.

Fig. 2 .

 2 Fig. 2. Recommendation accuracy under Time context information

Fig. 3 .

 3 Fig. 3. Recommendation accuracy without time context information

  Compared with the early behavior, the recent behavior of user reflects a better user's interest, based on which, this paper introduce the user's-visittime-base weight function describing the preference weight changes over time to improve the importance of recent behavior in recommendation. There are two types of weight function: Linear and Nonlinear. Linear function considers the user's preferences are forgetting linearly. Meanwhile the Nonlinear function thinks changes of user's preferences are nonlinearly. The research by YuHong (2010) shows that the algorithm of closely forgetting curve is superior to the linear function. That's why this paper chooses the nonlinear time function.

Defined by the curve, the attenuation function is a non-increasing function. Time function is defined in Equation (

2

).

Acknowledgements

Our appreciation goes to Ziyi Wang for her valuable comments to this paper.