G P Sahu
email: gsahu@mnnit.ac.in

Monika Singh

Green Informations Systems Adoption and Sustainability: a Case Study of Select Indian Banks

Keywords: Environment Changes, Industry's Vision and Strategy, Resource Allocation, Expert Selection, Communication, Conflicts Resolution, Standard Adoption, Human Resource Induction and Training, Efficient Organization Structure, Cost-Benefit Analysis, Inspection/Audits, Financial Support, Technological Advancement, Customer Demand, System Integration, Rivalry Pressure, Awareness, and Government Policies Green Information system, Green IS adoption, Sustainability process, Green IS, CSFs, Green Banking, ISM

This paper investigates the Critical Success Factors (CSFs) for successful adoption and implementation of Green Information System (Green IS) in organizations. Extensive literature review conducted to identify the CSFs and these CSFs are validated through case studies of two Indian banks-State Banks of India (SBI) and Housing Development Finance Corporation Limited (HDFC). Nineteen CSFs are identified, namely: Leaders Obligation,

Introduction

"We don't inherit the environment from our ancestors; we borrow it from our children". Stated by a renowned ecologist David Brower [START_REF] Brower | Let The Mountains Talk, Let The Rivers Run: a Call To Those Who Would Save The Earth[END_REF] indicating the necessity of Green initiatives adoption and its sustainability. While information system and information technology are the sources of industry/country growth, but on the other hand it is responsible for Greenhouse Gases (GHGs) emission contributing 1.6% share of total emission and expected to be account for 2% by 2020 [20]. It is required to use the IT/IS resources in a power competent and cost-effective manner [START_REF] Dedrick | Green IS: concepts and issues for information systems research[END_REF], [START_REF] Watson | Information Systems and Environmentally Sustainable Development: Energy Informatics and New Directions for the IS Community[END_REF], thus Green IS/IT emerged as an essential strategic tool to reduce organizations carbon footprints [START_REF] Butler | Compliance with institutional imperatives on environmental sustainability: Building theory on the role of Green IS[END_REF], [START_REF] Chen | Information systems and ecological sustainability[END_REF], [START_REF] Viaro | A conceptual framework to develop Green IT-going beyond the idea of environmental sustainability[END_REF] resulting in conservation of natural resources and the environment. The increasing demand of green product/services, public and consumers awareness towards for environmental issues [START_REF] Akenji | Consumer scapegoatism and limits to green consumerism[END_REF], [START_REF] Gabler | The environmental belief-behaviour gap: Exploring barriers to green consumerism[END_REF], [START_REF] Russo | A resource-based structure on corporate environmental performance and profitability[END_REF] and restricted policies over manufacturing and providing eco-friendly products/services [START_REF] Porter | Toward a new conception of the environmentcompetitiveness relationship[END_REF] encourages public and private organizations to manage their activities' impact on the environment and to achieve good reputation with avoiding additional expenditure [START_REF] Taib | The Collaboration of Green Design & Technology towards Business Sustainability in Malaysian Manufacturing Industry[END_REF].

Banking sector, being the less pollutant industry, is observing increasing rate of GHGs emission due to the massive use of electronic equipments and appliances [START_REF] Sudhalakshmi | Green Banking Practices in Indian[END_REF]. These issues necessitate the adoption of Green initiatives. Green IS adoption affects the reputation, quality of assets and rate of return on long term basis [START_REF] Sahoo | Green banking in India[END_REF]. The social responsibilities of banks encourages them to finance the green projects and adopt the innovative Green initiatives to control their business activities [START_REF] Bahl | Role of Green Banking in Sustainable Growth[END_REF][START_REF] Bihari | Green banking-towards socially responsible banking in India[END_REF].

Green IS refers to the developing and using Information Systems to assist and enable ecological sustainability programs tends to have an indirect and positive [START_REF] Jenkin | An agenda for 'Green' information technology and systems research[END_REF]. Green IS facilitates waste and energy reuse, and routing effectively [10], [START_REF] Chen | Organizational adoption of Green IS & IT: An institutional perspective[END_REF]. Green manufacturing strategy is essential on a long term implementation basis and a five-layer model is proposed by authors for implementation and planning [START_REF] Li | Planning and implementing the green manufacturing strategy: evidences from western China[END_REF]. The identified research gap is, limited literature available on factors influencing effective and efficient adoption of Green IS and barriers of implementation that because majority of available literature is on significance of the Green IS/IT. This paper fills this gap by identifying nineteen factors and few barriers through literature review and two Indian banks. This research paper is an attempt to identify the factors influencing the implementation of Green IS in the banking sector through extensive review of existing literature and in-depth personal interview of policy makers and IT experts of SBI and HDFC banks at Allahabad branch. The case studies these banks explored barriers in Green IS adoption. Nineteen CSFs identified and validated by these case studies. ISM model is used to determine relationship among these CSFs and to develop a model. Later, sustainability issues of Green initiatives are discussed. The entire research methodology is present in the third section. Paper is ended up with discussion and conclusion.

Literature Review

In the current era, when ICT is responsible for growth and development of countries by providing IT/IS services products, on the other hand it is accountable for contribution of 1.6% GHGs emission in the environment [20]. Worldwide firms and government move towards adopting Green practices due to exponentially increasing rate of GHGs emission and increasing demands of green products and services. [START_REF] Akenji | Consumer scapegoatism and limits to green consumerism[END_REF], [START_REF] Butler | Compliance with institutional imperatives on environmental sustainability: Building theory on the role of Green IS[END_REF], [START_REF] Chen | Information systems and ecological sustainability[END_REF], [START_REF] Gabler | The environmental belief-behaviour gap: Exploring barriers to green consumerism[END_REF], [START_REF] Russo | A resource-based structure on corporate environmental performance and profitability[END_REF], [START_REF] Viaro | A conceptual framework to develop Green IT-going beyond the idea of environmental sustainability[END_REF]. Accord-ing to Dedrick [START_REF] Dedrick | Green IS: concepts and issues for information systems research[END_REF] and Watson [START_REF] Watson | Information Systems and Environmentally Sustainable Development: Energy Informatics and New Directions for the IS Community[END_REF], it is required to use the IT/IS resources in power efficient and economical manner through implementing Green IS.

Firms adapting ISO 140001 certifications or other eco-friendly practices certificate rewards in many ways such as: reductions in incurred cost, waste production and in GHGs emission increment in savings; enhanced communication; reduction in penalties; well improved corporate reputation; and improved operational processes [START_REF] Chandrashekar | The environment is free: the quality analogy[END_REF], [START_REF] Daily | Achieving sustainability through attention to human resource factors in environmental management[END_REF], [START_REF] Hanna | Linking operational and environmental improvement through employee involvement[END_REF], [START_REF] Lee-Mortimer | Waste not, want not[END_REF], [START_REF] Maxwell | Green schemes: corporate environmental strategies and their implementation[END_REF], [START_REF] Nattrass | The Natural Step for Business: Wealth, Ecology and the Evolutionary Corporation[END_REF], [START_REF] Schaarsmith | ISO 14001 lowers environmental risks[END_REF], [START_REF] Zingale | Environmental management systems: making better business sense[END_REF][START_REF] Zutshi | Adoption and maintenance of environmental management systems: critical success factors[END_REF].

Henningsson & Hedman [START_REF] Hersey | A close look at ISO 14000: the quest to improve environmental safety[END_REF] found that Green IS is a bottom-up practice that attracts and make expert the individuals worried about environment, to investigate the problems and resolve it. Majority of the literature found on the antecedents of Green IS [START_REF] Kuo | The greening of organisational IT: what makes a difference?[END_REF], [START_REF] Molla | IT and eco-sustainability: Developing and validating a green IT readiness model[END_REF] and its role in environment sustainability [START_REF] Bose | Integrative framework for assessing firms' potential to undertake Green IT initiatives via virtualization -a theoretical perspective[END_REF], [START_REF] Chen | Information systems and ecological sustainability[END_REF], [START_REF] Hedman | Developing ecological sustainability: a green IS response model[END_REF], [START_REF] Marcus | Green management matters regardless[END_REF], [START_REF] Melville | Information systems innovation for environmental sustainability[END_REF].

Sarkar & Young [START_REF] Sarkar | Managerial attitudes towards Green IT: an explorative study of policy drivers[END_REF] suggested effective cost model and awareness programmes as influencing factors for Green IT adoption. Schmidt et al. [START_REF] Schmidt | Examining the contribution of Green IT to the objectives of IT departments: Empirical Evidence from German Enterprises[END_REF] found corporate administration, ecological commitment and initiatives from IT workforce as predictors of Green IS adoption. Butler [START_REF] Butler | Compliance with institutional imperatives on environmental sustainability: Building theory on the role of Green IS[END_REF] found that institutional essentials persuade the acceptance and implementation of Green IS initiatives. González [19] identified external factors (organization position, relations, policies) and internal factors (organizational strategy, technology and financial capacity) influencing adoption of clean technologies.

The benefits of GIS, augmented public awareness of environmental issues and regulatory instructions forced the organizations to Go Green through implementing Green IS [START_REF] Chen | Organizational adoption of Green IS & IT: An institutional perspective[END_REF]. Consequently Green IT/IS policy, design, and practice initiatives in recent times emerged into a vigorous research area in the Information System area. However, the existing literature represents a major gap of nonexistence research [START_REF] Chen | Information systems and ecological sustainability[END_REF], conceptual and empirical both, that can aid organizations to build up strategy and framework to adopt and implement Green IS and practices.

Research Design

Extensive literature review is conducted for identification of CSFs, while IT experts and academician's opinion (via personal interview) are used to validate these driving and restraining factors of Green IS implementation. ISM methodology is used to find out the relationship among the identified nineteen CSFs and thereafter, to develop a model to aid the researcher in this area and policy makers for smooth implementation of Green initiatives. The entire research design is presented in the Figure 1.

The research is based on the case studies of two banks: SBI, largest public bank in India and HDFC, among the top most private banks of India to exam-ine and analyze the factors driving and restraining the implementation of Green IS in banking sector. The first phase involves the extensive literature review and interview of 5-6 IT experts and policy makers from these two banks using structure and open ended questions in order to gain deep information about process and significance of Green IS implementation. Second phase includes synthesizing the case study to identify the CSFs and barriers of Green IS adoption and to validate them. ISM model is a tool to structure the various directly-indirectly interrelated elements into a complete systematic structure [START_REF] Attri | Interpretive Structural Modelling ( ISM ) approach : An Overview[END_REF], [START_REF] Sahoo | Green banking in India[END_REF], [START_REF] Singh | Knowledge management barriers: An interpretive structural modeling approach[END_REF].

According to Gupta and Sahu [START_REF] Gupta | Towards a Model for Adoption of Green IS Practices[END_REF] this is the best technique to examine the interdependency among the CSFs. Therefore, ISM model is used and a model is developed to draw the interrelationship among these nineteen CSFs.

Case Study 1: State Bank of India

The first largest and oldest bank of India, SBI, is on the 46th position all over world ranking with brand value of $6. Also, it has adopted the 'Phase-out' policy to change inefficient lighting options, green infrastructure concept for water management and energy savings. The employees promote and conduct green awareness campaigns in order to change the behavior and attitude of stakeholders towards environment sustainability. According to them, Green IS implementation influencing factors are leader's commitment, government policy, customer's awareness and green services demand and cost-benefit analysis.

Green IS Critical Success Factors

Through extensive literature review and interview of policy makers, IT experts of SBI and HDFC, and academician nineteen CSFs for implementation of Green IS are identified and listed in Table 1. Maximum of the influencing factors identified in the study are general in character and could be used in any type of organizations despite of the nature, sector and size of the industry. [13], [16], [START_REF] Fielding | ISO 14001 delivers effective environmental management and profits[END_REF], [START_REF] Gupta | Towards a Model for Adoption of Green IS Practices[END_REF], [START_REF] Henningsson | Industry-wide supply chain information integration: The lack of management and disjoint economic responsibility[END_REF], [START_REF] Kuo | The greening of organisational IT: what makes a difference?[END_REF], [START_REF] Molla | IT and eco-sustainability: Developing and validating a green IT readiness model[END_REF][START_REF] Nattrass | The Natural Step for Business: Wealth, Ecology and the Evolutionary Corporation[END_REF], [START_REF] Zutshi | Adoption and maintenance of environmental management systems: critical success factors[END_REF] 2. Environment Changes Dynamic process of changing of organization environment in adapting new technologies.

[19], [START_REF] Nattrass | The Natural Step for Business: Wealth, Ecology and the Evolutionary Corporation[END_REF], [START_REF] Russo | A resource-based structure on corporate environmental performance and profitability[END_REF], [START_REF] Wagner | Company-wide ISO 14001 certification[END_REF], [START_REF] Zutshi | Adoption and maintenance of environmental management systems: critical success factors[END_REF] 3. Industry's Vision and Strategy

Firm's vision and plans to encourage employees and to give them a sense of purpose.

[2], [START_REF] Bose | Integrative framework for assessing firms' potential to undertake Green IT initiatives via virtualization -a theoretical perspective[END_REF], [START_REF] Chen | Information systems and ecological sustainability[END_REF], [19], [START_REF] Henningsson | Industry-wide supply chain information integration: The lack of management and disjoint economic responsibility[END_REF], [START_REF] Molla | IT and eco-sustainability: Developing and validating a green IT readiness model[END_REF], [START_REF] Watson | Information Systems and Environmentally Sustainable Development: Energy Informatics and New Directions for the IS Community[END_REF], [START_REF] Zutshi | Adoption and maintenance of environmental management systems: critical success factors[END_REF] 4. Resource Alloca- tion Allocation of resources (like money, technologies, personnel etc.) and their continuous availability.

[27], [START_REF] Hersey | A close look at ISO 14000: the quest to improve environmental safety[END_REF], [START_REF] Schmidt | Predictors of Green IT Adoption: Implications from an Empirical Investigation[END_REF][START_REF] Scrimshire | What's involved in implementing ISO 14001?[END_REF], [START_REF] Zutshi | Adoption and maintenance of environmental management systems: critical success factors[END_REF] 5. Expert Selection Appointment of individual/s to iden- tify and resolve Green IS issues [START_REF] Henningsson | Industry-wide supply chain information integration: The lack of management and disjoint economic responsibility[END_REF], [START_REF] Petts | Environmental responsiveness, individual and organisational learning: SME experience[END_REF], [START_REF] Zutshi | Adoption and maintenance of environmental management systems: critical success factors[END_REF] 6. Communication 2-way communication between the organization & stakeholders.

[13], [19], [START_REF] Nattrass | The Natural Step for Business: Wealth, Ecology and the Evolutionary Corporation[END_REF], [START_REF] Wilson | Larry's features 'green' market special[END_REF], [START_REF] Zutshi | Adoption and maintenance of environmental management systems: critical success factors[END_REF] 7.

Human Re- source Induction and Training

Training of all stakeholders in order to trim down or eliminate their resistance and to develop awareness.

organizations if they want effective and smooth implementation of Green IS/initiatives. Many authors as shown in the table found in their studies these factors critical for implementation and also, IT experts, policy makers and academicians have supported and validated these factors as critical factors for Green IS implementation in their organizations.

ISM Methodology and Model Development

According to A.P. Sage [START_REF] Sage | Interpretive structural modeling: methodology for large-scale population density[END_REF], ISM modeling technique is an interactive learning process, aid to determine interdependency and direction among the variables of a system. This is a superior interactive planning method that enables people of a team to build up a structure to define/establish relationships among factors in a set [START_REF] Bolaños | Using interpretive structural modeling in strategic decision-making groups[END_REF]. To build up the structure, a set of questions are answered by Experts of the relevant field.

This model is used by various authors to interpret the relations and direction among the known variables relevant to the problem and to develop a structured model for better understanding of interdependency [START_REF] Gupta | Towards a Model for Adoption of Green IS Practices[END_REF], [START_REF] Iacobelli | Green / Sustainable IT / IS : Concepts and Cases Green / Sustainable IT / IS : Concepts and Cases[END_REF], [START_REF] Singh | Knowledge management barriers: An interpretive structural modeling approach[END_REF]. Therefore, ISM model is used and all steps followed to develop the model. The process consisted several steps: 1) Identified Critical Success Factors/elements via literature review and experts/academician's opinion (Table 1); 2) Developed Structural Self-Interaction Matrix (SSIM) pointing to pair-wise connection between elements; 3) Developed a Reachability matrix from SSIM, and checked whether the matrix is transitive or not i.e. if factor 1 is related to factor 2 and factor 2 is related to factor 3 then, definitely factors 1 and 3 are directly-indirectly related to each other according to ISM assumption (Table 2); 4) Developed Antecend Set and Intersection Set from SSIM, followed by partitioning of Reachability matrix into different level (Table 2). Based on the results from step 4, a directed graph is drawn resulting into a model by removing transitive relationship (Figure 2).

Human Resource Induction And Training 5,6,9,10,13,20

Discussion

In the current fast growing industries where government policies, stakeholders awareness towards environment sustainability, and market competitions are the major factors encouraging firms to adopt Green IS, few factors are pushing back the firms to accept the new Green IT/IS. On other side, if some firms have adopted the Green IT/IS and indulge in providing green services they are unable to sustain due to poor performance or lack of reward.

From the case studies it is observed that many factors like lack of trust (mainly of senior citizens), proper training and awareness programmes for public etc. are responsible for no or slow growth of Green IS adoption in the firms. Also, major factor responsible for slow growth is huge population, which takes time to train/learn, additionally other factors are lack of buy-in of management/employees, insufficient financial sources, lack of experts, undefined goal, lack of communication, inefficient IT infrastructure [START_REF] Bose | Integrative framework for assessing firms' potential to undertake Green IT initiatives via virtualization -a theoretical perspective[END_REF], [START_REF] Lee-Mortimer | Waste not, want not[END_REF]. Authors find in their research that the companies offering green services and implemented green policies are not earning more profit in comparison to other firms not indulged in green practices.

Conclusion

This research paper has identified nineteen Critical Success Factors for effective implementation of Green IS in organizations, with special reference to banking sector, to reduce their carbon footprints. The environmental accountability of industries, laws created by government, customer's awareness etc. are forcing firms to implement Green initiatives as an integral part of their business activities. This study will be helpful to IT Experts/Mangers to gain insight about Green IS/IT and its antecedents and to take appropriate actions to link Green IS with firm's strategy. The research is conducted with special reference to banking sector, but the results can be implemented to any company indulge in adopting green initiatives or Corporate Social Responsibility (CSR). Study is also helpful in creating increased revenue as the running cost of Green information technology and information system is very low. The proposed model in this study aid banks in adopting Green IS smoothly and efficiently.

Case studies of SBI and HDFC banks used to validate these factors and explored the sustainability issues of Green IS in these banks. Relationship among identified nineteen factors had been established using ISM model. Research model is developed representing the interdependency of all the factors showing that Awareness, Government Policies and Customer Demand are the major drivers of Green Is implementation in the firms.

Fig. 1 .

 1 Fig. 1. Research Process of the study

Fig. 2 .

 2 Fig. 2. Model for Critical Success Factors for Green IS implementation All factors were categorized under eight levels through Reachability matrix and a model developed from the Table2representing systematic directlyindirectly relationship among these CSFs. Figure2shows (Bottom -up approach) that factor 18, at level VIII, is the predictor of factor 19 and 15 (at level VII), where these two factors are interrelated and predictors of factors 5, 11, 13 and 17 (at level VI). Again these four factors are interrelated and predictors of 1, 8 and 14 (at level V). Similarly all these interdependent fac-

Case Study 2: Housing Development Finance Corporation Limited HDFC

  Solar ATMs, beginning of a pilot project to calculate the carbon footprint levels, funding to renewal energy projects. Currently SBI has more than 16,333 computerized branches and more than 22 millions netbanking users, since 2009-10 and faced various favored and disfavored factors in implementation of Green IS. By interview of IT experts and managers at SBI Allahabad main branch it is observed that various factors like government policies, financial support, customers and employees' awareness towards degradation of environment, technological innovation, customer demand are encouraging the branch to adopt Green initiatives. They are using old heritage building, in order to minimize the use of cooling systems, Kiosks, GCC for environment sustainability. However they are facing various problems like old aged customer's rigidness towards ac-ceptance of new technologies, lack of trust in online services, threat of online theft etc. Sometimes villagers or old aged person come to the banks (not using online banking) only to visit/walk or for gossiping with other customer. , established in 1994 in India, is second largest private lender in asset volume and 45th global rank holder. With the brand value of $12.6 billion for FY (2014-15), HDFC is one of the dynamic branches in the field of environment sustainability, accountable for operations effects on environment, adopted various Green initiatives as an essential elements of its business practices to control GHG emission and reduce carbon footprint. HDFC is signatory to the Carbon Disclosure Project and was amongst 16 firms in India to achieve Carbon Disclosure Leadership Index score 17 in 2012. Interview of IT experts and policy makers at HDFC Allahabad branch it is explored that through multi-channel delivery and E-statement it has reduced the consumption of papers; using Energy-Efficient Lighting concepts HDFC have achieved 10% reduction in electricity consumption.

	3.2

[START_REF] Sahoo | Green banking in India[END_REF]

for FY 2014-15. According to Annual Report-2015 of SBI, this bank is practicing accountable banking to reduce its carbon footprints and to improve eco-sustainability through introducing Green initiatives and adopting the electronic mode of operations. SBI has been providing Green Channel Counters (GCC), financial support to construction of wind farms in India, Online banking,

Table 1 .

 1 Critical Success Factors for implementation of Green IS

	S	CSFs	Description	Study
	N
	1. Leaders Obliga-	Top management support im-
		tion	portance in adopting environmental
			sustainability strategy

Table 2 .

 2 Reachability Set and Levels of Factors

	Factors	Reachability Set	Antecend Set	Inter-	Lev
					section	el
					Set
	1	Leaders Obli-	1,3,
		gation

  It is depicted from the Table2that all nineteen factors influencing implementation of Green IS into an organization are categorized under eight levels from I to VIII. Green IS implementation is on level I and Awareness is on Level VIII. The table2shows the antecend of the factors and their Reachability to the other factors. A model is developed (refer Figure2) from Table2i.e. ISM model of CSFs for better understanding of interdependency on each other.

	20 Green IS im-	2,12,16,20	1,3,4,5,6,7,8,9,1	12,16,2	I
	plementation		0,11,12,13,14,1	0
			5,16,17,18,19,2
			0
	-	3,5,6,9,11,12,13,2	5,7,8,10,12,13,1	5,12,13	IV
	tion/Audits	0	7,18,19,20	,20
	13 Financial	1,3,4,5,8,9,10,11,1	3,9,11,12,13,18,	3,9,11,	VI
	Support	2,13,14,16,20	19	12,13
	14 Technologi-	1,2,3,4,5,7,8,9,14,	1,3,4,5,6,8,10,1	3,4,5,8,	V
	cal Ad-	16,20	1,13,14,15,16,1	10,14,1
	vancement		7,18,19	6
	15 Customer	1,2,3,4,5,6,8,9,11,	2,10,15,18	2,15	VII
	Demand	14,15,16,17,20
	16 System Inte-	4,6,7,9,10,14,16,2	1,3,5,6,8,11,13,	6,14,16	III
	gration	0	14,15,16,17,18,	,20
			19,20
	17 Rivalry Pres-	1,2,3,4,5,6,7,8,9,1	2,7,10,15,17,18 2,7,17	VI
	sure	1,12,14,16,17,20
	18 Awareness	1,2,3,4,5,6,8,9,10,	5,18,19	5,18,19 VIII
		11,12,13,14,15,16,
		17,18,19,20
	19 Government	1,2,3,4,5,8,9,10,11	18,19	18,19	VII
	Policies	,12,13,14,16,18,19
		,20

Table 2

 2 representing systematic directlyindirectly relationship among these CSFs. Figure2shows (Bottom -up approach) that factor 18, at level VIII, is the predictor of factor 19 and 15 (at level VII), where these two factors are interrelated and predictors of factors 5, 11, 13 and 17 (at level VI). Again these four factors are interrelated and predictors of 1, 8 and 14 (at level V). Similarly all these interdependent fac-tors at level V are predictors of factors 2, 3, 6, 10 and 12 (at level IV). These interdependent factors at level IV are predictors of factor 16 (at level III). Further, factor 16 is the predictor of three interrelated factors 4, 7 and 9 (at level II). At level I the factor 20 i.e. Green IS implementation is the objective factor of this study is predicted by factors 4, 7 and 9 and indirectly with all rest sixteen factors. Therefore, this model provides a clear directed vision of interdependent CSFs of Green IS implementation in the banking industry as well as other similar organizations.


Vishnupriya Raghavan
email: l.vishnupriyaraghavan@gmail.com

Marya Wani
email: malikmarya@gmail.com

Dolphy Abraham
email: dolphy.abraham@alliance.edu.in

Expression in the Social Age: Towards an Integrated Model of Technology Acceptance, Personality, Civic Engagement and Social Capital

Keywords: Social media, civic engagement, social capital, technology acceptance, big five model, personality traits

We investigate the factors that affect the use of social media for civic engagement and social capital, and examine if online civic engagement also results in offline civic engagement. Using data from 282 university students, we find significant relationships between social media use, social capital, online and offline civic engagement. This study also tests the relationship between personality traits of individuals and how these traits relate to the use of social media for civic engagement and social capital. While agreeableness and conscientiousness are strongly associated with perceived usefulness of social media use, agreeableness was found to have a negative association with perceived usefulness of social media in the context of civic engagement.

Introduction

The use of social media presents new opportunities for citizens to express their opinions, discuss issues and initiatives of public interest, and display their commitment for a social cause [START_REF] Lee | Digital media use and participation leadership in social protests: The case of Tiananmen commemoration in Hong Kong[END_REF]. Studies have shown that social media use helps mobilize social protests and movements influencing offline civic participation [START_REF] Lee | Digital media use and participation leadership in social protests: The case of Tiananmen commemoration in Hong Kong[END_REF]. Social media use positively influences civic engagement through participatory behaviors, i.e., through free information exchange on news about civic matters, news and current events and interaction between users which may motivate more citizens to join a cause [START_REF] Kim | Discussion network heterogeneity matters: Examining a moderated mediation model of social media use and civic engagement[END_REF]. Prior research also suggests that online civic engagement promotes offline civic engagement [START_REF] Metzger | The new political voice of young Americans: Online engagement and civic development among first-year college students[END_REF] and it is seen as a precursor for engagement in physical communities, amongst young adults in particular [START_REF] Raynes-Goldie | Our space: Online civic engagement tools for youth[END_REF]. Few studies on social media have noted that the discussion of community/societal issues in social media can encourage individuals to become engaged citizens [START_REF] Culver | Media Literacy and Its Use as a Method to Encourage Civic Engagement[END_REF] and this may also lead to social capital [START_REF] Zúñiga | Social Media Use for News and Individuals' Social Capital, Civic Engagement and Political Participation[END_REF].

The above arguments motivate our interest in investigating the use of social media in a culturally diverse and a young developing country like India. The use of social media during the 2014 General Elections [START_REF] Ahmed | The 2014 Indian elections on Twitter: A comparison of campaign strategies of political parties[END_REF] provides evidence to suggest that the use of social media has been gaining momentum in the country. Focusing on the role of social media for civic engagement, we address three important gaps in the extant literature.

First, although civic and political organizations use social media, empirical research on the effects of social media use on civic engagement is limited [START_REF] Zúñiga | Social Media Use for News and Individuals' Social Capital, Civic Engagement and Political Participation[END_REF]. Second, online political groups may have an ability to foster offline political participation [START_REF] Conroy | Facebook and political engagement: A study of online political group membership and offline political engagement[END_REF]. However, further investigation on the effects of online participation on political participation and civic engagement can help researchers understand the civic and political processes [START_REF] Conroy | Facebook and political engagement: A study of online political group membership and offline political engagement[END_REF]. Third, there are few systemic studies that examine the factors that influence the use of social media [START_REF] Xu | Modeling user posting behavior on social media[END_REF] and effect of social media use on civic engagement [START_REF] Bolton | Understanding Generation Y and their use of social media: a review and research agenda[END_REF].

It is important for policy makers and governments to understand how social media is used for civic engagement. Uncovering the underlying motivations to use social media would help academia and researchers to understand user behavior, and the why and so-what of social media use. Some studies have focused on the effect of personality on social media use and the resulting social capital and civic engagement [START_REF] Zúñiga | Social Media Use for News and Individuals' Social Capital, Civic Engagement and Political Participation[END_REF]. However, studies report that the relation between personality and social media use (being a technology) may be mediated by technology acceptance factors [START_REF] Svendsen | Personality and technology acceptance: The influence of personality factors on the core constructs of the technology acceptance model[END_REF][START_REF] Zhou | The Effects of Personality Traits on User Acceptance of Mobile Commerce[END_REF]. The mediating effect of technology acceptance variables will help researchers explain the effect of social media use on civic engagement more comprehensively. We use an integrated model that studies the effect of personality traits using the Big Five model, on social media use mediated by variables of the technology acceptance model (TAM), the effects of online civic engagement on offline civic engagement and the effect of social capital on online civic engagement.

Prior Research and Hypotheses

In this section we present the prior literature in the areas of social media use, civic engagement, personality and technology acceptance. We also present an integrated model that builds on linking personality, technology acceptance models, social media and civic engagement.

Social Media, Social Capital and Civic Engagement

Civic engagement commonly refers to "knowledge of, interest in and discussion of public affairs, as well as participation" (Haller et al. 2011 p. 5 -[13]). Civic engagement through social media includes knowledge, interest, discussion and participation, and information gathered about public affairs through social media [START_REF] Haller | Does E-Government Use Contribute to Citizen Engagement with Government and Community?[END_REF]. Civic participation leads to empowering community members, developing critical awareness and performing citizenship [START_REF] Cicognani | Sense of Community and Empowerment Among Young People: Understanding Pathways from Civic Participation to Social Well-Being[END_REF].

Past work [START_REF] Jugert | Offline and Online Civic Engagement Among Adolescents and Young Adults from Three Ethnic Groups[END_REF] has demonstrated the positive relationship between social media use and two forms of civic engagement; offline civic engagement and online civic engagement. Hence we hypothesize: H1: Social media use is positively associated with online civic engagement Online communities that promote civic engagement have been found to facilitate offline civic engagement [START_REF] Raynes-Goldie | Our space: Online civic engagement tools for youth[END_REF][START_REF] Bennett | Communicating civic engagement: Contrasting models of citizenship in the youth web sphere[END_REF]. In order to study this phenomenon of online civic engagement through social media leading to offline civic engagement, we hypothesize:

H2: Online civic engagement through social media is positively associated with offline civic engagement

Social capital is defined as the "resources embedded in one's social networks, resources that can be accessed or mobilized through ties in the network" (Lin, 2008, p. 51 -[17]). Research suggests that social capital can be created from online relationships and interactions [START_REF] Yang | Social capital in information and communications technology research: past, present, and future[END_REF] and is referred to as 'virtual' or online social capital. We also measured social capital in the form of online social capital. Studies have found social media use to have a positive association with social capital [START_REF] Park | Being Immersed in Social Networking Environment: Facebook Groups, Uses and Gratifications, and Social Outcomes[END_REF] and also an antecedent for civic participation [START_REF] Raynes-Goldie | Our space: Online civic engagement tools for youth[END_REF]. Based on the literature above, we hypothesize:

H3: Social media use has a positive association with social capital H4: Social capital is positively associated with online civic participation

TAM and Social Media

A few studies have used a theory-driven approach to examine the psychological antecedents of civic engagement and of online civic engagement in particular [START_REF] Jugert | Offline and Online Civic Engagement Among Adolescents and Young Adults from Three Ethnic Groups[END_REF]. Prior studies have found that perceived usefulness is positively associated with the intention to use social media [START_REF] Lin | Why people use social networking sites: An empirical study integrating network externalities and motivation theory[END_REF]. Literature suggests that PEOU's influence on technology acceptance is moderated by PU [START_REF] Ma | The technology acceptance model: A meta-analysis of empirical findings[END_REF]. Hence, we hypothesize the following: H5 Perceived usefulness is positively associated with social media use H6: Perceived ease of use is positively associated with perceived usefulness

Personality and TAM

Personality can be conceptualized as an individual's behavioral, emotional, and attitudinal response patterns [START_REF] Balmaceda | How do personality traits affect communication among users in online social networks[END_REF]. For measuring personality we used the "Big Five" framework as it is one of the most widely used models in academic research [START_REF] Balmaceda | How do personality traits affect communication among users in online social networks[END_REF][START_REF] Correa | Who interacts on the Web?: The intersection of users' personality and social media use[END_REF] which defines five personality traits of conscientiousness, extraversion, openness, emotional stability and agreeableness [START_REF] Gosling | A very brief measure of the Big-Five personality domains[END_REF]. Prior research has empirically examined the effect of personality on behavioral intention (of using technology) mediated by TAM variables of perceived usefulness [25,[START_REF] Svendsen | Personality and technology acceptance: The influence of personality factors on the core constructs of the technology acceptance model[END_REF][START_REF] Zhou | The Effects of Personality Traits on User Acceptance of Mobile Commerce[END_REF] and ease of use [25,[START_REF] Svendsen | Personality and technology acceptance: The influence of personality factors on the core constructs of the technology acceptance model[END_REF]. These studies have mostly found support for the hypotheses studying the effect of personality traits on TAM variables.

People high in extraversion are likely to be high performers in tasks requiring social interaction like civic activities [START_REF] Barrick | The Big Five Personality Dimensions and Job Performance: A Meta-Analysis[END_REF]. Such people are also likely to act based on their perceptions of what others think about them. In the context of civic engagement, high performers are likely to use the tools like social media to present themselves as competent in front of their peers.

H7: Extraversion is positively associated with perceived usefulness of social media for civic engagement

Agreeable people are generally viewed as kind, considerate, likable or cooperative [START_REF] Russo | The Personality Divide: Do Personality Traits Differentially Predict Online Political Engagement?[END_REF]. In the context of civic engagement, these traits may be less apparent as individuals motivated to take part in an activity pertaining to solving a civic problem are more likely to be angry or disturbed about the status quo. Therefore, we posit that individuals who are less agreeable are more motivated to use social media for civic engagement activities.

H8: Agreeableness is negatively associated with perceived usefulness of social media for civic engagement

Conscientious people possess an intrinsic motivation for accomplishment. They are more likely to try to use the tools available to improve the performance of the task at hand [25]. They are more able to follow directions and make use technology effectively than people who are non-conscientious [START_REF] Rosen | The impact of the big five personality traits on the acceptance of social networking website[END_REF]. We therefore posit that conscientious people are more likely to see the benefits of using social media to support their civic activities.

H9: Conscientiousness is positively associated with perceived usefulness of social media for civic engagement

We use the construct of emotional stability to measure the emotional status of the individual based on prior studies [25]. Individuals taking part in civic engagement activity and who wish to interact and work with others need to be able to allow others to observe their work and to be able to handle criticism from others. Hence, emotional stability H10: Emotional stability is positively associated with perceived usefulness of social media for civic engagement People who rank highly on openness are more likely to learn new things and find new ways to carry out tasks [START_REF] Barrick | The Big Five Personality Dimensions and Job Performance: A Meta-Analysis[END_REF]. The use of social media presents the opportunity for individuals to try a new platform to accomplish a social objective. Therefore, we posit that individuals who rank highly on openness will also be more likely to use social media for their civic activities.

H11: Openness is positively associated with perceived usefulness of social media for civic engagement 3 Method

The above review of literature reveals that although a number of studies have studied the impact of social media on civic engagement, and likewise of personality on social media use, the mediation effect of TAM factors has not been studied in a comprehensive and integrated model. In the following sections we explain our research design and analysis of data.

Sample and Procedure

To examine the relationship between social media use and civic engagement and to examine the factors that influence social media use, an online survey was conducted among undergraduate and graduate students including Executive MBA and PhD students of a university in Bangalore, India between January 2016 and March 2016. All the students received the survey's URL through an email invitation and three reminders were sent subsequently. A total of 2954 survey links were sent and 298 responses were received out of which 282 usable responses were used for data analysis making the response rate 9.6%. Socio demographics included gender (female = 45%), age (range: 18 to 84),and educational qualification (undergraduate = 60.9%, graduate = 36.8%).

Measures

All the subjective scales employed in this study are extracted from prior literature. The perceived ease of use and perceived usefulness were measured based on earlier studies [START_REF] Davis | Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology[END_REF], which was employed in the TAM literature [START_REF] Venkatesh | User acceptance of information technology: Toward a unified view[END_REF]25] in the context of personality traits and technology use. The personality traits were measured using part of the 10-item personality inventory [START_REF] Gosling | A very brief measure of the Big-Five personality domains[END_REF] that has been shown to have adequate levels of reliability, validity and external correlates [START_REF] Gosling | A very brief measure of the Big-Five personality domains[END_REF].

Social media use is operationalized using the attitudinal scale developed by earlier studies [START_REF] Ellison | The Benefits of Facebook "Friends:" Social Capital and College Students' Use of Online Social Network Sites[END_REF]. The respondents' online and offline civic engagement and social capital was gauged using the scale developed by earlier studies [START_REF] Jugert | Offline and Online Civic Engagement Among Adolescents and Young Adults from Three Ethnic Groups[END_REF][START_REF] Zúñiga | Social Media Use for News and Individuals' Social Capital, Civic Engagement and Political Participation[END_REF].

Preliminary Measurement Validation

The pilot study helped establish content and face validity. Our examination of the psychometric properties of the scales showed Cronbach's alpha > 0.7 confirming acceptable reliabilities.

Reliability and Validity

Table 1 shows that acceptable ranges for composite reliability, and average variance extracted (AVE). The two important validity measures, convergent validity and discriminant validity can also be inferred from Table 2. The AVE of all constructs are larger than 0.5 as shown in Table 2 confirming convergent validity. Discriminant validity can be inferred as the indicators load higher on their measured construct than on other constructs; and the square root of the average variance extracted (AVE) is larger than its correlations with other constructs [START_REF] Chin | The partial least squares approach to structural equation modeling[END_REF].

The Fornell-Larcker Criterion

Discriminant validity can also be assessed by the Fornell-Larcker criterion [START_REF] Fornell | Structural equation models with unobservable variables and measurement error: Algebra and statistics[END_REF] which states that a construct has to share more variance with its corresponding indicators than with other constructs (Refer Table 2).

The Structural Model: Hypotheses Testing

Hypotheses are tested using the structural model. A 5 % significance level is used as a statistical decision criterion. The validated model with the structural path coefficients and their significance is illustrated in Figure 1. The hypotheses that are supported are shown in Table 3.

Additional Validity Tests

Effect Size

The PLS structural model can be assessed by f 2 that is obtained by (R 2 incl -R 2 excl)/ (1-R 2 incl) [START_REF] Cohen | Statistical Power Analysis for the Behavioural Sciences[END_REF]. The f 2 values of 0.02, 0.15 and 0.35 denote small, medium and large effects respectively [START_REF] Ringle | Editor's comments: a critical look at the use of PLS-SEM in MIS quarterly[END_REF]. The effect sizes of various independent variables are presented in Table 5.

Goodness of Fit

A GoF value of the structural model was obtained and found to be 0.3478 which exceeds the cut-off value of 0.25 for medium effect sizes of r squared [START_REF] Tenenhaus | PLS path modeling[END_REF].

The Stone-Geisser Test

The Stone-Geisser test [START_REF] Tenenhaus | PLS path modeling[END_REF] also called as the Q 2 indicator is also used to assess the predictive relevance of the structural model. Using the blind folding procedure, the cross-validated redundancy of Perceived Usefulness (0.1559), Social Media Use (0.2312), Online Civic Participation (0.1176), Offline Civic Participation (0.2209) and Social Capital (0.2205) are found and are greater than 0 signifying the predictive relevance of the model.

Results and Discussion

We empirically tested the effect of social media use on online civic engagement (H1) and social capital (H3); social capital on online civic engagement (H4) and also the effect of online civic engagement on offline civic engagement (H2) and found support for all the hypotheses. We also studied the effect of personality traits identified by the Big Five model on social media use with extraversion, agreeableness, conscientiousness, and openness, having a significant effect on perceived usefulness of social media while emotional stability had no significant effect on perceived usefulness. It is important to note that we found agreeableness to have a negative significant effect on social media use for civic participation as was hypothesized. The results affirm our belief that in the context of civic engagement, agreeableness may not be a personality trait that the users of social media possess as individuals motivated to take part in an activity pertaining to solving a civic problem are more likely to have angst or be disturbed about the status quo. Perceived ease of use had a significant impact on perceived usefulness of social media. Perceived usefulness had a significant positive impact on social media use (H5).

It is interesting to note that social media is able to generate civic interest. This is an important finding for governments, civic action groups and other parties interested in using social media as an enabling tool for democracy. This may be because of the participatory nature of the medium as compared to other traditional media which may encourage users of social media to exhibit civic engagement. Another reason as to why social media fosters civic engagement could be the trust factor [START_REF] Zúñiga | Social Media Use for News and Individuals' Social Capital, Civic Engagement and Political Participation[END_REF]. Social media use can create reciprocity and trust among its members which in turn fosters civic engagement and social capital [START_REF] Zúñiga | Social Media Use for News and Individuals' Social Capital, Civic Engagement and Political Participation[END_REF].

Prior research shows that a significant part of discussions related to civic matters do happen online particularly amongst young adults. This means that, the more the respondents were involved in online civic engagement, the more they participate in offline civic engagement. The results corroborate with earlier findings [START_REF] Vesnic-Alujevic | Political participation and web 2.0 in Europe: A case study of Facebook[END_REF][START_REF] Park | Being Immersed in Social Networking Environment: Facebook Groups, Uses and Gratifications, and Social Outcomes[END_REF].The fact that social media can be used as a platform for civic engagement is significant in the light of the fact that younger generations are more ardent users of social media and hence social media can be considered as potentially potent tool for civic activities in the future. The results help us understand how citizens use social media to spur civic action both online and offline [START_REF] Zúñiga | Social Media Use for News and Individuals' Social Capital, Civic Engagement and Political Participation[END_REF][START_REF] Correa | Who interacts on the Web?: The intersection of users' personality and social media use[END_REF].

Conclusions

We believe that our study has advanced the scholarly debate on the transformative role played by social media. Our research has developed and empirically validated a new integrated theoretical framework that relates personality traits and technological factors on social media use and its outcome on civic engagement and social capital. We studied the role of social media in civic engagement using both, personality traits and technology perspectives, rather than just one of the approaches. The limitations of this study should be recognized. This study examined diverse age groups but the interpretation of the findings should be treated with caution as a majority of respondents belonged to the age group of 18 and 35. Our findings may be subjected to a selfselection bias, as younger adults having significant experience in using Internet technologies are more likely to respond to a web survey. Although this age group is best suited in the context of social media use, richer insights could be obtained with middle aged adults and senior citizens as well. While the model stresses the fact that personality traits do account for civic engagement, future research could include social traits such as life satisfaction, trust and personality factors such as loneliness. These types of traits can motivate people to express their emotions in social media. Future research can evaluate findings from information collected through qualitative and quantitative methods and also investigate moderator roles of socio-economic status, age group, education, income levels and network size. Despite these limitations, we believe our work strongly contributes to the growing field of social media research. The finding that online civic engagement positively influences offline civic engagement and also influences social capital is certainly promising for a country like India with weak infrastructure and civic apathy. Online civic engagement, if can spur offline actions that can become visible mass movements, engendering civic participation and engagement as the results demonstrate, can be a boon for developing economies in particular where citizens can work with the government to bring changes in the society.

*Fig. 1 .

 1 Fig. 1. The Validated Research Model

Table 1 .

 1 Reliability and Convergent Validity

	Variable	Cronbach's α	Composite reliability	AVE
	Perceived ease of use	0.7384	0.8477	0.6502
	Perceived Usefulness	0.7552	0.8601	0.6726
	Social media Use	0.8468	0.8909	0.6211
	Social Capital	0.9003	0.9226	0.6659
	Online Civic Engagement	0.8980	0.922	0.6641
	Offline Civic Engagement	0.8725	0.9066	0.6622

Table 2 .

 2 Inter-construct correlations: The Fornell-Larker Criterion for Discriminant Validity

		AVE	PEOU	PU	SM_USE	SOC_CAP CIV_ONL CIV_OFF
	Perceived ease of use	0.6502	0.8063
	Perceived usefulness	0.6726	0.4431	0.8201
	Social media use	0.6211	0.3695	0.6214	0.7881
	Social capital	0.6659	0.3669	0.6658	0.5915	0.8160
	Civic engagement online	0.6641	0.2254	0.2986	0.3700	0.4007	0.8149
	Civic engagement offline	0.6622	0.0646	0.2194	0.1565	0.2015	0.5942	0.8138

Table 3 .Test of PLS Path with Bootstrap

 3

	Path	Mean for Path	Standard deviation for	T statistic	Hypothesis
		Coefficient	path coefficients
	EXT →PU	0.1087	0.665	1.6946 *	Supported
	AGR→PU	-0.1401	0.0512	2.6826 **	Supported
	OPN→PU	-0.0445	0.0611	0.6954	Not Supported
	CON→PU	0.1277	0.0677	1.8225 *	Supported
	EMS→PU	0.1281	0.0549	2.3836 **	Supported
	PEOU→PU	0.4459	0.0527	8.3313 ***	Supported
	PU→SM_USE	0.6269	0.0362	17.1876 ***	Supported
	SM_USE →CIV_ONL	0.2086	0.066	3.1012 **	Supported
	SM_USE→SOC_CAP	0.5948	0.0441	13.4065 ***	Supported
	SOC_CAP→CIV_ONL	0.2796	0.0627	4.4581 **	Supported
	CIV_ONL→CIV_OFF	0.5996	0.0496	11.9774 ***	Supported

Table 5 . Effect size -Relevant indicators for the structural model

 5

	Path	R 2 included	R 2 excluded	T value	f 2
	EXT →PU	0.258	0.25	1.6946	0.0107
	AGR→PU		0.244	3.573	0.0188
	OPN→PU		0.257	0.6954	0.0013
	CON→PU		0.246	1.8225	0.0161
	EMS→PU		0.244	2.3836	0.0188
	PEOU→PU		0.074	8.3313	0.2479