While there has been a substantial amount of attention within the information systems research community towards understanding the phenomenon of adoption, much less is known about non-adoption. This study examines the factors surrounding the decision to not adopt a technology and whether certain factors exert differing effects on individuals in particular ways such that concurrent factors could be identified to develop a classification of the specific types of non-adoption behavior. Utilizing inhibitor theory and the symbolic adoption model as a foundational framework for the different types of non-adoption, we posit that different types of non-adoption exist which is demonstrated by determining the perceptions towards technology that coalesce around different types of non-adoption. We conducted a two-phase investigation into non-adoption with two goals in mind: 1) identify and explore specific factors of the IT that are associated with the rejection decision and are distinct from the adoption decision, and 2) determine the extent to which these factors (along with traditional enablers) differentiate between different types of non-adoption. The results from a discriminant function analysis (DFA) indicate the coalescence of specific perceptual variables according to the types of non-adoption behavior, specifically, the discriminatory power of differing perceptions of IT between trial rejecters, symbolic rejecters, trial accepters, symbolic adopters, and adopters. The implications for research and implications for practice are discussed.
{"title":"An Exploration of the Drivers of Non-Adoption Behavior: A Discriminant Analysis Approach","authors":"C. Wolverton, Ronald T. Cenfetelli","doi":"10.1145/3353401.3353405","DOIUrl":"https://doi.org/10.1145/3353401.3353405","url":null,"abstract":"While there has been a substantial amount of attention within the information systems research community towards understanding the phenomenon of adoption, much less is known about non-adoption. This study examines the factors surrounding the decision to not adopt a technology and whether certain factors exert differing effects on individuals in particular ways such that concurrent factors could be identified to develop a classification of the specific types of non-adoption behavior. Utilizing inhibitor theory and the symbolic adoption model as a foundational framework for the different types of non-adoption, we posit that different types of non-adoption exist which is demonstrated by determining the perceptions towards technology that coalesce around different types of non-adoption. We conducted a two-phase investigation into non-adoption with two goals in mind: 1) identify and explore specific factors of the IT that are associated with the rejection decision and are distinct from the adoption decision, and 2) determine the extent to which these factors (along with traditional enablers) differentiate between different types of non-adoption. The results from a discriminant function analysis (DFA) indicate the coalescence of specific perceptual variables according to the types of non-adoption behavior, specifically, the discriminatory power of differing perceptions of IT between trial rejecters, symbolic rejecters, trial accepters, symbolic adopters, and adopters. The implications for research and implications for practice are discussed.","PeriodicalId":46842,"journal":{"name":"Data Base for Advances in Information Systems","volume":null,"pages":null},"PeriodicalIF":2.8,"publicationDate":"2019-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87196483","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
O. Ogbanufe, Catalin C. Dinulescu, Xiaotong Liu, Carullah Y. Kucuk
This paper examines the impact of mobile device characteristics on perceptions of cloud storage. Following the framework and guidelines for context-specific theorizing in information systems research, we develop and test a model that examines the following research questions: How does the individual's experience with mobile devices impact perceptions of mobile cloud storage? How do mobile context-specific factors influence the individual's adoption of cloud storage? The model incorporates context-specific factors such as ease of file storage, ease of file transfer, multiple device use, and mobile device use. Our study contributes to the literature on theorizing context-specific factors by highlighting the importance of mobile device characteristics and usage contexts in individual technology adoption research. We also identify both performance increases and security challenges in providing access to cloud storage through mobile devices to individuals.
{"title":"It's in the Cloud: Theorizing Context-Specific Factors Influencing the Perception of Mobile Cloud Storage","authors":"O. Ogbanufe, Catalin C. Dinulescu, Xiaotong Liu, Carullah Y. Kucuk","doi":"10.1145/3353401.3353408","DOIUrl":"https://doi.org/10.1145/3353401.3353408","url":null,"abstract":"This paper examines the impact of mobile device characteristics on perceptions of cloud storage. Following the framework and guidelines for context-specific theorizing in information systems research, we develop and test a model that examines the following research questions: How does the individual's experience with mobile devices impact perceptions of mobile cloud storage? How do mobile context-specific factors influence the individual's adoption of cloud storage? The model incorporates context-specific factors such as ease of file storage, ease of file transfer, multiple device use, and mobile device use. Our study contributes to the literature on theorizing context-specific factors by highlighting the importance of mobile device characteristics and usage contexts in individual technology adoption research. We also identify both performance increases and security challenges in providing access to cloud storage through mobile devices to individuals.","PeriodicalId":46842,"journal":{"name":"Data Base for Advances in Information Systems","volume":null,"pages":null},"PeriodicalIF":2.8,"publicationDate":"2019-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88105868","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In Part 1 the argument was made for the core Positivist principle of enabling falsification, specifically that data, or at least correlation or covariance matrices, should be made public so that others can attempt to falsify at least the statistical analyses. Doing so could provide a semblance of the direction of what might constitute the desired Positivist aspects of intellectual integrity in science: making your claims and putting your data in the public domain so others may put its propositions to the test and try to falsify or improve on them. Part 2 demonstrates the importance of such disclosure. The demo begins with replicating the model in Structural Equation Modeling and Regression: Guidelines for Research Practice (Gefen et al., 2000) in PLS and CBSEM R packages, producing equivalent results as the original paper. Showing the point about the need to have the data in the public domain, a set of incorrectly specified models on the same data are then run. Both PLS and CBSEM converge and produce plausibly believable results if the data were not available to test alternative models, opening the possibility of pulling the wool over readers' eyes if such a correlation or covariance matrix is not provided.
{"title":"A Post-Positivist Answering Back.: Part 2: A Demo in R of the Importance of Enabling Replication in PLS and LISREL","authors":"D. Gefen","doi":"10.1145/3353401.3353404","DOIUrl":"https://doi.org/10.1145/3353401.3353404","url":null,"abstract":"In Part 1 the argument was made for the core Positivist principle of enabling falsification, specifically that data, or at least correlation or covariance matrices, should be made public so that others can attempt to falsify at least the statistical analyses. Doing so could provide a semblance of the direction of what might constitute the desired Positivist aspects of intellectual integrity in science: making your claims and putting your data in the public domain so others may put its propositions to the test and try to falsify or improve on them. Part 2 demonstrates the importance of such disclosure. The demo begins with replicating the model in Structural Equation Modeling and Regression: Guidelines for Research Practice (Gefen et al., 2000) in PLS and CBSEM R packages, producing equivalent results as the original paper. Showing the point about the need to have the data in the public domain, a set of incorrectly specified models on the same data are then run. Both PLS and CBSEM converge and produce plausibly believable results if the data were not available to test alternative models, opening the possibility of pulling the wool over readers' eyes if such a correlation or covariance matrix is not provided.","PeriodicalId":46842,"journal":{"name":"Data Base for Advances in Information Systems","volume":null,"pages":null},"PeriodicalIF":2.8,"publicationDate":"2019-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74378750","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Cynthia K. Riemenschneider, M. Buche, Deborah J. Armstrong
The preponderance of the academic research focused on diversity in the IS field has emphasized the perspectives of women and racioethnic minorities. Recent research has found that following the appointment of a female CEO, white male top managers provided less help to colleagues, particularly those identified as minority-status (McDonald, Keeves, & Westphal, 2018). Additionally, Collison and Hearn (1994) assert that white men's universal status and their occupancy of the normative standard state have rendered them invisible as objects of analysis. To develop a more holistic view of the IS workplace, we expand the academic exploration by looking at the challenges men face in the Information Systems (IS) workplace. Using a cognitive lens, we evoke the challenges men perceive they face at work and cast them into revealed causal maps. We then repeat the process evoking women's perspectives of men's challenges. The findings are analyzed using the Communication Theory of Identity (CTI) to determine the areas of overlap and identity gaps. This study advances our understanding of the cognitive overlap (and lack thereof) regarding the challenges facing men in the IS field, and provides another step toward developing a more inclusive IS work environment.
{"title":"He Said, She Said: Communication Theory of Identity and the Challenges Men Face in the Information Systems Workplace","authors":"Cynthia K. Riemenschneider, M. Buche, Deborah J. Armstrong","doi":"10.1145/3353401.3353407","DOIUrl":"https://doi.org/10.1145/3353401.3353407","url":null,"abstract":"The preponderance of the academic research focused on diversity in the IS field has emphasized the perspectives of women and racioethnic minorities. Recent research has found that following the appointment of a female CEO, white male top managers provided less help to colleagues, particularly those identified as minority-status (McDonald, Keeves, & Westphal, 2018). Additionally, Collison and Hearn (1994) assert that white men's universal status and their occupancy of the normative standard state have rendered them invisible as objects of analysis. To develop a more holistic view of the IS workplace, we expand the academic exploration by looking at the challenges men face in the Information Systems (IS) workplace. Using a cognitive lens, we evoke the challenges men perceive they face at work and cast them into revealed causal maps. We then repeat the process evoking women's perspectives of men's challenges. The findings are analyzed using the Communication Theory of Identity (CTI) to determine the areas of overlap and identity gaps. This study advances our understanding of the cognitive overlap (and lack thereof) regarding the challenges facing men in the IS field, and provides another step toward developing a more inclusive IS work environment.","PeriodicalId":46842,"journal":{"name":"Data Base for Advances in Information Systems","volume":null,"pages":null},"PeriodicalIF":2.8,"publicationDate":"2019-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75030171","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Knowing who is an expert on social media is a challenging yet important task, especially in a world where misleading information is commonplace and where social media is an important information source for knowledge seekers. In this paper we investigate expertise heuristics by comparing features of experts versus non-experts in big data settings. We employ a large set of features to classify experts and non-experts using data collected on two social media platform (Twitter and reddit). Our results show a good ability to predict who is an expert, especially using language-based features, validating that heuristics can be developed to differentiate experts from novices organically, based on social media use. Our results contribute to the development of expertise location and identification systems as well as our understanding on how experts present themselves on social media.
{"title":"Recognizing Experts on Social Media: A Heuristics-Based Approach","authors":"Benjamin D. Horne, Dorit Nevo, Sibel Adali","doi":"10.1145/3353401.3353406","DOIUrl":"https://doi.org/10.1145/3353401.3353406","url":null,"abstract":"Knowing who is an expert on social media is a challenging yet important task, especially in a world where misleading information is commonplace and where social media is an important information source for knowledge seekers. In this paper we investigate expertise heuristics by comparing features of experts versus non-experts in big data settings. We employ a large set of features to classify experts and non-experts using data collected on two social media platform (Twitter and reddit). Our results show a good ability to predict who is an expert, especially using language-based features, validating that heuristics can be developed to differentiate experts from novices organically, based on social media use. Our results contribute to the development of expertise location and identification systems as well as our understanding on how experts present themselves on social media.","PeriodicalId":46842,"journal":{"name":"Data Base for Advances in Information Systems","volume":null,"pages":null},"PeriodicalIF":2.8,"publicationDate":"2019-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76319110","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
I am a critical post-Positivist ? and hold it as a badge of honor. To be a Positivist means that you are humbly willing to put your theory to a test that can falsify it ? that is, to show that it is wrong despite all that you have put into it. To be a post-Positivist means believing in that standard but also acknowledging the limitations of Positivism, including limitations of measurement and its theory-dependence as well as acknowledging that there are social processes in science too. A post- Positivist does not claim that other epistemologies are necessarily wrong. It is just that researchers who adhere to the falsification principle are willing to put their money where their claims are, rather than allowing in the temptation to endlessly massage theories so that they are constantly updated to be consistent with new facts. In that vein, Positivism, despite its limitations, can by virtue of the falsification principle put a dent in confirmation bias and the kind of heuristics suggested by Tversky and Kahneman that prejudice our seeing patterns even when they do not exist. It is in that spirit that this paper is written.
{"title":"The Philosopher's Corner: A Post-Positivist Answering Back. Part 1: Good for You, Karl Popper!","authors":"D. Gefen","doi":"10.1145/3330472.3330475","DOIUrl":"https://doi.org/10.1145/3330472.3330475","url":null,"abstract":"I am a critical post-Positivist ? and hold it as a badge of honor. To be a Positivist means that you are humbly willing to put your theory to a test that can falsify it ? that is, to show that it is wrong despite all that you have put into it. To be a post-Positivist means believing in that standard but also acknowledging the limitations of Positivism, including limitations of measurement and its theory-dependence as well as acknowledging that there are social processes in science too. A post- Positivist does not claim that other epistemologies are necessarily wrong. It is just that researchers who adhere to the falsification principle are willing to put their money where their claims are, rather than allowing in the temptation to endlessly massage theories so that they are constantly updated to be consistent with new facts. In that vein, Positivism, despite its limitations, can by virtue of the falsification principle put a dent in confirmation bias and the kind of heuristics suggested by Tversky and Kahneman that prejudice our seeing patterns even when they do not exist. It is in that spirit that this paper is written.","PeriodicalId":46842,"journal":{"name":"Data Base for Advances in Information Systems","volume":null,"pages":null},"PeriodicalIF":2.8,"publicationDate":"2019-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78517030","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
I come before you in this forum as the Jester in the Court of the Philosopher Kings. Keeping in mind the medieval commensuration of the term ?fool" with ?jester" and you will have a closer appreciation of the self-deprecating point I seek to make in this sense. I am but a lay reader of the literature of philosophy. However much I appreciate it, enthuse over it, or embrace it as the principle upon which my science is grounded, all the same, I am a simple journeyman, to borrow from Eric Clapton's similar self-deprecation, when it comes to the field of philosophy.
{"title":"The Philosophy that Guides our Science?","authors":"T. Stafford","doi":"10.1145/3330472.3330474","DOIUrl":"https://doi.org/10.1145/3330472.3330474","url":null,"abstract":"I come before you in this forum as the Jester in the Court of the Philosopher Kings.\u0000 Keeping in mind the medieval commensuration of the term ?fool\" with ?jester\" and you will have a closer appreciation of the self-deprecating point I seek to make in this sense. I am but a lay reader of the literature of philosophy. However much I appreciate it, enthuse over it, or embrace it as the principle upon which my science is grounded, all the same, I am a simple journeyman, to borrow from Eric Clapton's similar self-deprecation, when it comes to the field of philosophy.","PeriodicalId":46842,"journal":{"name":"Data Base for Advances in Information Systems","volume":null,"pages":null},"PeriodicalIF":2.8,"publicationDate":"2019-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88768335","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Lack of careful consideration of common method effects in empirical research can lead to several negative consequences for the interpretation of research outcomes, such as biased estimates of the validity and reliability of the measures employed as well as bias in the estimates of the relationships between constructs of interest, which in turn can affect hypothesis testing. Taken together, these make it very difficult to make any interpretations of the results when those are affected by substantive common method effects. In the literature, there are several preventive, detective, and corrective techniques that can be employed to assuage concerns about the possibility of common method effects underlying observed results. Among these, the most popular has been Harman's Single-Factor Test. Though researchers have argued against its effectiveness in the past, the technique has continued to be very popular in the discipline. Moreover, there is a dearth of empirical evidence on the actual effectiveness of the technique, which we sought to remedy with this research. Our results, based on extensive Monte Carlo simulations, indicate that the approach shows limited effectiveness in detecting the presence of common method effects and may thus be providing a false sense of security to researchers. We therefore argue against the use of the technique moving forward and provide evidence to support our position.
{"title":"Detecting Common Method Bias: Performance of the Harman's Single-Factor Test","authors":"Miguel I. Aguirre-Urreta, Jiang Hu","doi":"10.1145/3330472.3330477","DOIUrl":"https://doi.org/10.1145/3330472.3330477","url":null,"abstract":"Lack of careful consideration of common method effects in empirical research can lead to several negative consequences for the interpretation of research outcomes, such as biased estimates of the validity and reliability of the measures employed as well as bias in the estimates of the relationships between constructs of interest, which in turn can affect hypothesis testing. Taken together, these make it very difficult to make any interpretations of the results when those are affected by substantive common method effects. In the literature, there are several preventive, detective, and corrective techniques that can be employed to assuage concerns about the possibility of common method effects underlying observed results. Among these, the most popular has been Harman's Single-Factor Test. Though researchers have argued against its effectiveness in the past, the technique has continued to be very popular in the discipline. Moreover, there is a dearth of empirical evidence on the actual effectiveness of the technique, which we sought to remedy with this research. Our results, based on extensive Monte Carlo simulations, indicate that the approach shows limited effectiveness in detecting the presence of common method effects and may thus be providing a false sense of security to researchers. We therefore argue against the use of the technique moving forward and provide evidence to support our position.","PeriodicalId":46842,"journal":{"name":"Data Base for Advances in Information Systems","volume":null,"pages":null},"PeriodicalIF":2.8,"publicationDate":"2019-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82105031","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Computer self-efficacy is one of the more important constructs in information systems (IS) research. Over the years, IS researchers have debated about its multifaceted nature. Yet, despite, extensive debate, we contend that for information systems, the conceptualization of various self-efficacy dimensions is incomplete. The primary dimension currently focused on is the specificity of the technology. This has resulted in two types of self-efficacy being investigated: computer self-efficacy and specific computer self-efficacy. However, the task being performed with technology has received limited attention in information systems self-efficacy research and discussions. We argue that there are four distinct types of computer self-efficacy constructs that are derived from combining the dimensions of specificity of information technology (specific/general) and task type (simple/complex) into a 2x2 model. Using data gathered from a quasi-experimental study, we illustrate how these constructs are not only theoretically different but also have a distinct measurement item set. Implications for expanding self-efficacy research are discussed at the end.
{"title":"A Revision of Computer Self-Efficacy Conceptualizations in Information Systems","authors":"Saurabh Gupta, R. Bostrom","doi":"10.1145/3330472.3330478","DOIUrl":"https://doi.org/10.1145/3330472.3330478","url":null,"abstract":"Computer self-efficacy is one of the more important constructs in information systems (IS) research. Over the years, IS researchers have debated about its multifaceted nature. Yet, despite, extensive debate, we contend that for information systems, the conceptualization of various self-efficacy dimensions is incomplete. The primary dimension currently focused on is the specificity of the technology. This has resulted in two types of self-efficacy being investigated: computer self-efficacy and specific computer self-efficacy. However, the task being performed with technology has received limited attention in information systems self-efficacy research and discussions. We argue that there are four distinct types of computer self-efficacy constructs that are derived from combining the dimensions of specificity of information technology (specific/general) and task type (simple/complex) into a 2x2 model. Using data gathered from a quasi-experimental study, we illustrate how these constructs are not only theoretically different but also have a distinct measurement item set. Implications for expanding self-efficacy research are discussed at the end.","PeriodicalId":46842,"journal":{"name":"Data Base for Advances in Information Systems","volume":null,"pages":null},"PeriodicalIF":2.8,"publicationDate":"2019-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90444875","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This study develops and validates an instrument for assessing organization improvisational capability (OIC) for potential use in future empirical studies. A definition of OIC and its dimensions are proposed based on an intensive literature review. An initial three-dimension, nine-item OIC scale derived from the literature is validated iteratively and then refined through a rigorous process into a two-factor, eight-item scale. The final scale demonstrates adequate psychometric properties, including reliability and convergent and discriminant validity. As such, this study contributes to a deeper theoretical understanding of the OIC construct and the appropriate application of such scales in future empirical studies. Future research on organization performance, agility, and strategy could utilize the proposed scale to study how OIC creates business value.
{"title":"Organization Improvisational Capability: Scale Development and Validation","authors":"LeeAnn Kung, Hsiang-Jui Kung","doi":"10.1145/3330472.3330479","DOIUrl":"https://doi.org/10.1145/3330472.3330479","url":null,"abstract":"This study develops and validates an instrument for assessing organization improvisational capability (OIC) for potential use in future empirical studies. A definition of OIC and its dimensions are proposed based on an intensive literature review. An initial three-dimension, nine-item OIC scale derived from the literature is validated iteratively and then refined through a rigorous process into a two-factor, eight-item scale. The final scale demonstrates adequate psychometric properties, including reliability and convergent and discriminant validity. As such, this study contributes to a deeper theoretical understanding of the OIC construct and the appropriate application of such scales in future empirical studies. Future research on organization performance, agility, and strategy could utilize the proposed scale to study how OIC creates business value.","PeriodicalId":46842,"journal":{"name":"Data Base for Advances in Information Systems","volume":null,"pages":null},"PeriodicalIF":2.8,"publicationDate":"2019-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75161644","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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