Open Access
Open access
Computers in Human Behavior Reports, volume 10, pages 100291

Use of partial least squares structural equation modelling (PLS-SEM) in privacy and disclosure research on social network sites: A systematic review

Mahamadou Kante 1, 2
Michel Babri 3
1
 
Institut des Sciences Humaines (ISH), Sotuba-ACI, BP E916, Bamako, Mali
2
 
Université Virtuelle de Côte d’Ivoire (UVCI), 28 BP 536 Abidjan 28, Abidjan, Côte d'Ivoire
3
 
Institut National Polytechnique Félix Houphouët-Boigny (INP-HB), BP 1093, Yamoussoukro, Côte d'Ivoire
Publication typeJournal Article
Publication date2023-05-01
scimago Q1
wos Q1
SJR1.365
CiteScore7.8
Impact factor4.9
ISSN24519588
Computer Science Applications
Artificial Intelligence
Human-Computer Interaction
Cognitive Neuroscience
Neuroscience (miscellaneous)
Applied Psychology
Abstract
Structural equation modelling (SEM) is a statistical technique used in the field of Information Systems amongst others. The technique has been paid attention thanks to its flexibility and predictive power. However, there is a paucity of guidelines in the application of the technique in the field of Behavioural Information Security. Hence, this paper aims to provide a comprehensive guide of using PLS-SEM in disclosure and privacy studies on Social Network Sites (SNSs). Data has been gathered using papers (n=21) published between 2006 and 2022 from scholarly databases such as Google Scholar, Association for Information Systems eLibrary (AISeL), IEEE Xplore and Science Direct. The Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA 2020) was used to analyse and synthesize the status of the field. Our systematic review covers data characteristics, reasons for using PLS-SEM, the evaluation of measurement models, the evaluation of the structural model and reporting best practices. The review proposed guidelines for the use of PLS-SEM in the discipline of Behavioural Information Security with a focus on disclosure and privacy on SNSs studies and other fields as well.
Cheng X., Hou T., Mou J.
Information and Management scimago Q1 wos Q1
2021-09-01 citations by CoLab: 45 Abstract  
This study investigates what affects perceived risks and how the trade-off between perceived risks and benefits affects individuals’ information privacy choices in the context of IT-enabled ride-sharing. Using privacy calculus theory and immediate gratification, we adopt a mixed-methods approach. We use interview data to identify perceived information disclosure risks’ antecedents, and then implement our research model, conducting privacy calculus on data from 507 rideshare users. The results indicate that privacy awareness, previous online privacy invasion, mobile payment security, and negative media exposure influence information disclosure’s perceived risks and that perceived risks and benefits are significantly related to immediate gratification.
Chung K., Chen C., Tsai H., Chuang Y.
Computer Communications scimago Q1 wos Q1
2021-06-01 citations by CoLab: 32 Abstract  
Artificial intelligence (AI) is widely used in social network as AD Recommender Systems , Viral Marketing, and User Sentiment Detection. However, such things as Fake News and Privacy Leaking may violate privacy and security concerns. AI technology is also often used in social media as the main technology to prevent personal privacy from leaking. This study explored whether social media users will disclose information or further protect privacy when facing information privacy issues. It studied information security awareness and perceived privacy control while affecting privacy concerns and customer calibration related factors, and finds their privacy management and self-disclosure. This study used questionnaire survey method to understand user data and used Structural Equation Modeling (SEM) to analyze the relationship of various dimensions. The results showed that understanding information security awareness and customer alienation through AI technology has a positive impact on consumers’ privacy concerns. Through privacy management, consumers can indeed reduce their doubts about privacy leakage . Customer privacy concerns and customer calibration have positive and significant effects on privacy management and self-disclosure, respectively. This study showed that user trust in the platform will affect the degree of user information disclosure . The industry should focus more on the user’s privacy maintenance and establish a complete protection mechanism.
Page M.J., McKenzie J.E., Bossuyt P.M., Boutron I., Hoffmann T.C., Mulrow C.D., Shamseer L., Tetzlaff J.M., Akl E.A., Brennan S.E., Chou R., Glanville J., Grimshaw J.M., Hróbjartsson A., Lalu M.M., et. al.
Systematic Reviews scimago Q1 wos Q1 Open Access
2021-03-29 citations by CoLab: 6515 PDF
Fan A., Wu Q., Yan X., Lu X., Ma Y., Xiao X.
2021-01-01 citations by CoLab: 7 Abstract  
The disclosure of personal information by users is very important for social media, in order to balance privacy protection and personalized service. This article probes into the factors influencing users’ disclosure intention. Based on the privacy calculus theory and theory of planned behavior, the study constructs an influencing factor model of social media personal information disclosure intention. Then an extensive survey of social media users is conducted through questionnaire, and the hypothetical model is verified using structural equation model, and finally the relationship between various influencing factors and personal information disclosure intentions is obtained. The results show that the perceived benefits and subjective norm are related to personal information disclosure intentions, and privacy view is associated with perceived risk. Finally, the study provides new ideas for social media services and user privacy protection, such as creating a secure social media environment, increasing valuable social services, reducing users’ risk perception and making information processing open and transparent.
Lankton N.K., McKnight D.H., Tripp J.F.
2020-08-01 citations by CoLab: 11 Abstract  
Privacy in online social networking (OSN) is more complex than in traditional online environments, such as e-commerce. In addition to simply limiting self-disclosure, OSN users can also use privacy settings and manage their network size to ensure privacy. This complexity calls for an enhanced OSN privacy model that more completely explains privacy behaviors. Combining the privacy calculus model with part of the uses and gratifications approach, this paper proposes an OSN privacy model that depicts both antecedents (i.e., privacy concern, trusting beliefs, and personal interest) and outcomes (i.e., gratifications obtained) of perceived privacy and use behaviors. Using an Empanel survey sample collected from U.S. Facebook users, results show that privacy concern influences network size, trust influences privacy setting use and use frequency, and personal interest influences each privacy and use behavior. Findings also show that the privacy behaviors' influence on gratifications obtained is complex in nature. A three-way interaction influences enjoyment and habit gratifications, and a two-way interaction influences bonding social capital. This paper provides opportunities for future research regarding OSN privacy behaviors, and it discusses practical implications.
Hsieh S.H., Lee C.T.
Telematics and Informatics scimago Q1 wos Q1
2020-06-01 citations by CoLab: 12 Abstract  
The prevailing adoption of mobile devices has facilitated individuals’ engagement with location tagging; thus, location-based information sharing, which allows geolocation specificity and interaction on the Internet platforms, has become a popular activity in the space of social media. This spatiotemporal information provides a great potential opportunity for marketers as photos or videos shared among friends on social networking sites can be viewed as a type of word-of-mouth that may increase brand awareness and attract more users. Thus, understanding the underlying factors driving location tagging intentions provides significant value for practitioners. However, despite its importance, our understanding of this topic is limited. This research draws from social exchange theory and the theory of impression management to exemplify the underlying factors driving individuals to engage in photo or video sharing with location tagging on social media. Using an online survey, we recruited 402 users. We find that location tagging intention is driven by a facilitating route involving social benefits and functional benefits and an impeding route involving perceived risk related to privacy concerns. Our findings provide important academic and managerial implications.
Lin X., Wang X.
2020-02-01 citations by CoLab: 107 Abstract  
Information systems research provides increasing evidence that women and men differ in their use of information technology. However, research has not sufficiently explained why these differences exist. Using the theory of reasoned action and social role theory, this paper investigates gender differences in people’s decisions about information sharing in the context of social networking sites (SNSs). We developed a comparative model of the information-sharing decision process across genders and theoretically explained why these differences exist. Data was collected from an online survey taken by American SNS users. We found that privacy risks, social ties, and commitment were more important in the formation of attitudes toward information sharing for women than men. Gender significantly moderates the relationship between people’s perceptions of information sharing and their intention to share information. This paper provides an enhanced understanding of gender differences in people’s decisions about sharing information on SNSs. It advances gender differences research into the use of newly emerged information technology and provides researchers insightful views of the role that gender plays in the social media era. Being aware of the research findings, practitioners may better engage their targeted stakeholders on SNSs and collect more useful information for business purposes.
Aivazpour Z., Rao V.S.
2020-01-21 citations by CoLab: 25 Abstract  
Self-disclosure of personal information is generally accepted as a security risk. Nonetheless, many individuals who are concerned about their privacy will often voluntarily reveal information to others. This inconsistency between individuals' expressed privacy concern and the willingness to divulge personal information is referred to as privacy paradox. Several arguments have been proposed to explain the inconsistency. One set of arguments centers around the possible effects of differences in personality characteristics, such as the Big Five factors. In the current article, we examine the role of one personality characteristic, impulsivity, in explaining the relationship between privacy concern and information disclosure. We report the results of a survey-based study that consisted of two hundred and forty-two (242) usable responses from subjects recruited on Amazon Mechanical Turk. The results show that one of the three dimensions of impulsivity, motor impulsivity, directly influences the extent of information disclosure and also moderates the relationship between privacy concern and information disclosure. Furthermore, our study shows impulsivity explains more variance in information disclosure than explained by the Big Five factors only.
Li K., Cheng L., Teng C.
2020-01-01 citations by CoLab: 63 Abstract  
Private information disclosure on social networking sites (SNS) is one of the most important and active issues in the information management arena. The growing phenomenon of platforms requiring users to disclose personal information exposes the limitations of previous studies that only focus on users’ voluntary disclosure. In this study, we define two modes of users’ private information disclosure behavior: voluntary sharing and mandatory provision. Using the Communication Privacy Management theory, we built a framework to explain the impact of individual characteristics, context, motivation, and benefit–risk ratio on the user's willingness to disclose voluntarily or mandatorily. Our research shows that voluntary sharing is more likely to be driven by positive factors, such as perceived benefits, social network size, and personalization, while mandatory provision is affected by individual characteristics such as age, privacy policy, and perceived risks. One of our interesting findings is that perceived risk has less impact on voluntary sharing than previous studies suggested. When encouraging users to share information voluntarily, platforms do not need to pay as much attention to reducing perceived risk as in the mandatory providing mode, but should focus on improving perceived benefits. Being the first to classify and compare the private information disclosure modes of SNS users, our research enriches the existing literature and opens up new avenues for researchers and social networking platforms.
Hair J.F., Risher J.J., Sarstedt M., Ringle C.M.
European Business Review scimago Q1 wos Q2
2019-01-14 citations by CoLab: 10654 Abstract  
Purpose The purpose of this paper is to provide a comprehensive, yet concise, overview of the considerations and metrics required for partial least squares structural equation modeling (PLS-SEM) analysis and result reporting. Preliminary considerations are summarized first, including reasons for choosing PLS-SEM, recommended sample size in selected contexts, distributional assumptions, use of secondary data, statistical power and the need for goodness-of-fit testing. Next, the metrics as well as the rules of thumb that should be applied to assess the PLS-SEM results are covered. Besides presenting established PLS-SEM evaluation criteria, the overview includes the following new guidelines: PLSpredict (i.e., a novel approach for assessing a model’s out-of-sample prediction), metrics for model comparisons, and several complementary methods for checking the results’ robustness. Design/methodology/approach This paper provides an overview of previously and recently proposed metrics as well as rules of thumb for evaluating the research results based on the application of PLS-SEM. Findings Most of the previously applied metrics for evaluating PLS-SEM results are still relevant. Nevertheless, scholars need to be knowledgeable about recently proposed metrics (e.g. model comparison criteria) and methods (e.g. endogeneity assessment, latent class analysis and PLSpredict), and when and how to apply them to extend their analyses. Research limitations/implications Methodological developments associated with PLS-SEM are rapidly emerging. The metrics reported in this paper are useful for current applications, but must always be up to date with the latest developments in the PLS-SEM method. Originality/value In light of more recent research and methodological developments in the PLS-SEM domain, guidelines for the method’s use need to be continuously extended and updated. This paper is the most current and comprehensive summary of the PLS-SEM method and the metrics applied to assess its solutions.
Xu H., Dinev T., Smith J., Hart P.
2018-02-04 citations by CoLab: 379 Abstract  
Organizational information practices can result in a variety of privacy problems that can increase consumers’ concerns for information privacy. To explore the link between individuals and organizations regarding privacy, we study how institutional privacy assurances such as privacy policies and industry self-regulation can contribute to reducing individual privacy concerns. Drawing on Communication Privacy Management (CPM) theory, we develop a research model suggesting that an individual’s privacy concerns form through a cognitive process involving perceived privacy risk, privacy control, and his or her disposition to value privacy. Furthermore, individuals’ perceptions of institutional privacy assurances -namely, perceived effectiveness of privacy policies and perceived effectiveness of industry privacy self-regulation -are posited to affect the riskcontrol assessment from information disclosure, thus, being an essential component of privacy concerns. We empirically tested the research model through a survey that was administered to 823 users of four different types of websites: 1) electronic commerce sites, 2) social networking sites, 3) financial sites, and 4) healthcare sites. The results provide support for the majority of the hypothesized relationships. The study reported here is novel to the extent that existing empirical research has not explored the link between individuals’ privacy perceptions and institutional privacy assurances. We discuss implications for theory and practice and provide suggestions for future research.
Ali F., Rasoolimanesh S.M., Sarstedt M., Ringle C.M., Ryu K.
2018-01-08 citations by CoLab: 851 Abstract  
Purpose Structural equation modeling (SEM) depicts one of the most salient research methods across a variety of disciplines, including hospitality management. While for many researchers, SEM is equivalent to carrying out covariance-based SEM, recent research advocates the use of partial least squares structural equation modeling (PLS-SEM) as an attractive alternative. We systematically examine how PLS-SEM has been applied in major hospitality research journals with the aim of providing important guidance and, if necessary, opportunities for realignment in future applications. As PLS-SEM in hospitality research is still in an early stage of development, critically examining its use holds considerable promise in order to counteract misapplications which otherwise might reinforce over time. Design/methodology/approach We reviewed all PLS-SEM studies published in six SSCI-indexed hospitality management journals between 2001 and 2015. Tying in with prior studies in the field, our review covers reasons for usin...
Hair J., Hollingsworth C.L., Randolph A.B., Chong A.Y.
2017-04-10 citations by CoLab: 1951 Abstract  
Purpose Following the call for awareness of accepted reporting practices by Ringle, Sarstedt, and Straub in 2012, the purpose of this paper is to review and analyze the use of partial least squares structural equation modeling (PLS-SEM) in Industrial Management & Data Systems (IMDS) and extend MIS Quarterly (MISQ) applications to include the period 2012-2014. Design/methodology/approach Review of PLS-SEM applications in information systems (IS) studies published in IMDS and MISQ for the period 2010-2014 identifying a total of 57 articles reporting the use of or commenting on PLS-SEM. Findings The results indicate an increased maturity of the IS field in using PLS-SEM for model complexity and formative measures and not just small sample sizes and non-normal data. Research limitations/implications Findings demonstrate the continued use and acceptance of PLS-SEM as an accepted research method within IS. PLS-SEM is discussed as the preferred SEM method when the research objective is prediction. Practical implications This update on PLS-SEM use and recent developments will help authors to better understand and apply the method. Researchers are encouraged to engage in complete reporting procedures. Originality/value Applications of PLS-SEM for exploratory research and theory development are increasing. IS scholars should continue to exercise sound practice by reporting reasons for using PLS-SEM and recognizing its wider applicability for research. Recommended reporting guidelines following Ringle et al. (2012) and Gefen et al. (2011) are included. Several important methodological updates are included as well.
Castro Silva W.A., Ferreira L.J., Cançado V.L., De Muylder C.F.
Bottom Line scimago Q1 wos Q1
2025-01-10 citations by CoLab: 0 Abstract  
Purpose This study aims to examine the impact of investment in innovation, market structure and competitive position on the supermarket value chain in the USA. Design/methodology/approach This paper used secondary data from Economatica® for the period 2010–2020, encompassing 83 firms within the US supermarket value chain, resulting in 913 observations for each model covariate. The data were analyzed through structural equation modeling, using the partial least squares (PLS) approach, using SMARTPLS® software. Findings The results indicate that both market structure and investment in innovation have a significant impact on a firm’s competitive position. Specifically, a more concentrated market structure is associated with a weaker competitive position, whereas higher levels of investment in innovation correspond to a stronger competitive position. However, no significant relationship was found between investment in innovation and market structure. Research limitations/implications This study is limited to the Economatica® database, from which this paper selected a sample of firms within the US supermarket value chain. This paper recommend future research to compare data from other countries or sectors. For the three-dimensional model, this paper used constructs with indicators of investment, performance and market concentration; however, this paper suggests incorporating additional variables to enhance the model’s robustness. Practical implications An analysis of market structure and its impact on competitive positioning offers valuable insights for managers regarding the strategic dimensions of the supermarket industry. Integrating the effects of investment in innovation into business strategies can enhance long-term economic benefits. Adopting a value chain perspective further facilitates the examination of market equilibrium and competitive positioning within the supermarket industry. Social implications The findings of this study can help prevent the adoption of misguided strategies that fail to foster business growth. By highlighting the significant impact of innovation on performance, while considering the competitive dynamics within the supermarket industry, the study provides a deeper understanding of the risks faced by various firms across the value chain and the dual nature of competition within the sector. Moreover, it reinforces the relevance of research on economic sustainability and supports the development of effective growth strategies for firms. Originality/value While most studies focus on hypotheses examining the relationships between innovation and competitive positioning or between innovation and market structure, this study introduces a three-dimensional model that uses structural equation modeling to test these interconnections simultaneously. Furthermore, it extends the analysis by incorporating the value chain as a central component, using a diverse sample of firms directly linked to the core operations of the supermarket industry.
Anjaningrum W.D., Azizah N., Suryadi N.
Heliyon scimago Q1 wos Q1 Open Access
2024-04-01 citations by CoLab: 0 Abstract  
Abstract Several studies have explored firm performance in the post-Covid-19 pandemic era. However, there is not much research to find reports divulging the complex relationship dynamics between business intelligence, organizational and network learning, customer value anticipation, and creative economy-based small-medium enterprises (SMEs) performance in developing countries. This study aims to uncover the complexity of those relationships. The quantitative data were collected from 313 creative economy-based SMEs in East Java, Indonesia. Using PLS-SEM, this study disclosed that business intelligence practices could not directly impact SMEs' performance. Business intelligence will be crucial to SMEs' performance with the support of organizational learning as a mediator. The finding also confirmed the presence of serial mediation of organizational learning and innovation in the relationship between business intelligence and SMEs' performance. However, the role of network learning and innovation is also important, considering their relatively large direct impact on SMEs' performance. The theoretical implications of this research broke the boundaries of strategic management theory in resource-based view and knowledge-based view in the latest era, where creative economy-based SMEs have been able to mobilize resources to carry out business intelligence to realize innovation and high performance. Further research is suggested to explore the role of business intelligence in promoting specific performance areas, such as marketing performance, financial performance, and human resource management. In addition, it is advisable to choose more specific research subjects, including those in the culinary subsector, and pay attention to other areas, e.g., the demographics of respondents in the model as a control variable.
Joana Carolina C., Gabriela R., Ismael M.
Journal of Business Research scimago Q1 wos Q1
2024-02-01 citations by CoLab: 5 Abstract  
Sustainable entrepreneurship (SE) has been researched in different areas but with little attention on sustainability. This study analyses the effects of economic, social, and technological factors on SE over time. It applies partial least squares structural equation modelling (PLS-SEM) to test three hypotheses. The results show that, while all three factor categories positively impact SE over time, the impact of technological factors is less significant.
Firdausi M., Ahyudanari E., Herijanto W.
2023-10-12 citations by CoLab: 0 Abstract  
Travel behavior analysis involves the utilization and examination of travel demand through the application of theories and analytical techniques derived from diverse scientific disciplines. There are many methods used by researchers in analyzing travel behavior. Mode selection is the stage where the transportation planning process is responsible for determining the travel load or knowing the number of people and goods, then selecting the available transportation models that serve as the starting point of the destination. Travel factors have a strong influence on a person’s travel behavior, (trip maker behavior), including income, vehicle ownership, vehicle condition, settlement density of one’s socioeconomic conditions. This paper describes the disadvantages and advantages of travel behavior modeling analysis and factors that influence the choice of modes based on travel behavior, so that in the future researchers can use it as an illustration in determining the right analysis.
Abumalloh R.A., Nilashi M., Ooi K.B., Wei-Han G., Cham T., Dwivedi Y.K., Hughes L.
Annals of Operations Research scimago Q1 wos Q1
2023-09-27 citations by CoLab: 28 Abstract  
The concept of the metaverse involves creating a fully immersive virtual world that allows users to interact with each other and digital objects in a way that is almost indistinguishable from reality. One of the key areas where the metaverse is expected to have an impact is retailing. Although there have been several studies on the use of the metaverse in different industries, this issue is rarely investigated in previous studies in the context of retail companies focusing on users’ perceptions. This study accordingly explores the factors impacting the adoption of a metaverse in the retail industry and develops a new model based on the Resource-Based View (RBV) theory. In addition, the relationship between the usage intention of the metaverse and product innovation, and the relationship between product innovation and sustainable competitive advantage are investigated. Furthermore, as sustainability is a critical issue in the adoption of innovation by industries, this study aims to further investigate whether sustainability commitment will strengthen the impact of attitude toward metaverse on the intention to use. The data was collected from retail companies in Malaysia and analyzed to evaluate the proposed research model. The outcomes of this research indicated that there is a positive impact of product innovation on sustainable competitive advantage through the adoption of a metaverse in retail companies. In addition, our findings stressed that the intention to use metaverse will lead to product innovation in retail companies. Furthermore, the results revealed that sustainability commitment does not moderate the relationship between attitude toward the metaverse and intention to use, but impacts the usage intention of the metaverse directly.
Takyi-Annan G.E., Zhang H.
Buildings scimago Q1 wos Q2 Open Access
2023-06-25 citations by CoLab: 2 PDF Abstract  
Building information modeling (BIM) mandates are becoming more widespread because BIM allows design and construction teams to operate more productively and also enables them to collect the data they generate during the process for use in operations and maintenance tasks. As a result, professionals in the architecture, engineering and construction (AEC) industries are expected to possess excellent BIM expertise. Despite the fact that the developing world has largely not adopted BIM, many studies have been conducted on BIM usage, awareness, drivers and barriers with a focus on the developing world. Numerous studies have pointed to the professionals’ lack of BIM expertise in the developing world’s AEC sector as a major barrier to BIM deployment. Nevertheless, no research has been conducted to assess the variables impacting the level of BIM expertise among professionals. After a detailed review of the literature, the study developed five study hypotheses and created a conceptual model to help assess the variables impacting the level of BIM expertise of professionals in the AEC industry in the developing world. After that, a questionnaire survey was carried out to collect data from 103 seasoned professionals in the Ghanaian construction industry. Nonparametric tests, such as the Kruskal–Wallis, pairwise post hoc Dunn, Mann–Whitney, Pearson’s correlation and the partial least squares structural equation modeling (PLS SEM) tests, were adopted to assess the relationships between the level of BIM expertise of professionals (BE) and the following variables: (1) profession (P), (2) the frequency of BIM use by professionals (BF), (3) the highest dimension of BIM adopted by AEC firms and companies (BD), (4) professionals’ perception of BIM (PB) and (5) the BIM implementation barriers (BIMIBs). P, BF, BD and PB were found to have a substantial impact on the level of BIM expertise acquired by professionals. With regards to professionals’ perception of the BIM software and process, only one (PB3–BIM is not useful to our company at the moment) out of ten of them was found to have a significant impact on BE, highlighting the impact of employers on the level of BIM expertise of professionals. In addition, the study discovered that any resolution made in an attempt to tackle the lack of/insufficient level of BIM expertise among professionals would prove futile without significant effort from the higher education sector (HES) of the developing world and the entire world at large. The study’s conceptual, empirical, managerial and theoretical implications and findings would serve as a roadmap for researchers, professionals and academics in developing nations as they endeavor to seek more ways of increasing BIM expertise among their professionals and to encourage BIM usage throughout the project lifecycle.

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