Pub Date : 2020-07-13DOI: 10.1080/10919392.2020.1788359
Takuya Futagami, N. Hayasaka
ABSTRACT Consumer-to-consumer (C2C) online market places have become popular. Several C2C online market places adopt product recognition from uploaded images representing the current state of the products to aid in the entering of product information for creating listing pages. To improve recognition accuracy, it is important for extracting product regions from product images as a pre-processing for recognition. Given these circumstances, this study proposes a method of extracting product regions from images used in C2C online market places. We analyzed product images for effective product extraction and developed the proposed method using the region-growing algorithm and GrabCut segmentation algorithm based on these analysis results. To generate initial seeds for GrabCut, the proposed method specifies image-border areas as background areas based on the analysis results and applies the region-growing algorithm to the specified background areas. To evaluate the effectiveness of the proposed method, we compared its extraction accuracy and computational time with those of a conventional method using 412 product images, including 341 actual images. The proposed method was effective in both extraction accuracy (20.3% improvement rate) and computational time (76.7% reduction) compared with the conventional method. Compared with the conventional method, the proposed method increased the extraction accuracy for all the product categories from sellers. Therefore, the effectiveness of the proposed method can be observed for several product images. Furthermore, we confirmed that each process of the proposed method is necessary for improving the extraction accuracy.
{"title":"Automatic Product Region Extraction based on analysis of Images Uploaded to C2C Online Market","authors":"Takuya Futagami, N. Hayasaka","doi":"10.1080/10919392.2020.1788359","DOIUrl":"https://doi.org/10.1080/10919392.2020.1788359","url":null,"abstract":"ABSTRACT Consumer-to-consumer (C2C) online market places have become popular. Several C2C online market places adopt product recognition from uploaded images representing the current state of the products to aid in the entering of product information for creating listing pages. To improve recognition accuracy, it is important for extracting product regions from product images as a pre-processing for recognition. Given these circumstances, this study proposes a method of extracting product regions from images used in C2C online market places. We analyzed product images for effective product extraction and developed the proposed method using the region-growing algorithm and GrabCut segmentation algorithm based on these analysis results. To generate initial seeds for GrabCut, the proposed method specifies image-border areas as background areas based on the analysis results and applies the region-growing algorithm to the specified background areas. To evaluate the effectiveness of the proposed method, we compared its extraction accuracy and computational time with those of a conventional method using 412 product images, including 341 actual images. The proposed method was effective in both extraction accuracy (20.3% improvement rate) and computational time (76.7% reduction) compared with the conventional method. Compared with the conventional method, the proposed method increased the extraction accuracy for all the product categories from sellers. Therefore, the effectiveness of the proposed method can be observed for several product images. Furthermore, we confirmed that each process of the proposed method is necessary for improving the extraction accuracy.","PeriodicalId":54777,"journal":{"name":"Journal of Organizational Computing and Electronic Commerce","volume":"30 1","pages":"323 - 334"},"PeriodicalIF":2.9,"publicationDate":"2020-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/10919392.2020.1788359","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43263864","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}
Pub Date : 2020-06-11DOI: 10.1080/10919392.2020.1776033
A. Jeyaraj, A. Zadeh
ABSTRACT This research examines how organizational cybersecurity responses become isomorphic over time. Drawing on institutional theory, this study theorizes that mimetic pressures, normative pressures, and coercive pressures impact cybersecurity responses. Using the textual data gathered from the annual 10-K reports published by 87 large organizations and their competitors, topic modeling was employed to assess the cybersecurity responses and institutional pressures. Linear regression was applied to the resultant topic weights. Findings show that mimetic pressures were significant over time while coercive pressures were significant in the near-term and normative pressures were significant in the long-term. Implications for research and practice are discussed.
{"title":"Institutional Isomorphism in Organizational Cybersecurity: A Text Analytics Approach","authors":"A. Jeyaraj, A. Zadeh","doi":"10.1080/10919392.2020.1776033","DOIUrl":"https://doi.org/10.1080/10919392.2020.1776033","url":null,"abstract":"ABSTRACT This research examines how organizational cybersecurity responses become isomorphic over time. Drawing on institutional theory, this study theorizes that mimetic pressures, normative pressures, and coercive pressures impact cybersecurity responses. Using the textual data gathered from the annual 10-K reports published by 87 large organizations and their competitors, topic modeling was employed to assess the cybersecurity responses and institutional pressures. Linear regression was applied to the resultant topic weights. Findings show that mimetic pressures were significant over time while coercive pressures were significant in the near-term and normative pressures were significant in the long-term. Implications for research and practice are discussed.","PeriodicalId":54777,"journal":{"name":"Journal of Organizational Computing and Electronic Commerce","volume":"30 1","pages":"361 - 380"},"PeriodicalIF":2.9,"publicationDate":"2020-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/10919392.2020.1776033","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43387699","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}
Pub Date : 2020-05-20DOI: 10.1080/10919392.2020.1748977
Somayeh Kalantari, E. Nazemi, B. Masoumi
ABSTRACT Context Today, we are facing the growing development of distributed systems which their vast scale has challenged their centralized management. Therefore, many researchers design these systems as self-organizing. After implementing self-organizing systems, new behaviors known as emergence form at a global level of the system. Objective The purpose of this paper is to study the concept of emergence in various natural and artificial systems, categorize research activities, identify research pathways of emergence in computer science, and shed light on future research directions. Method In this paper, for a systematic literature review, numerous articles regarding emergence phenomena in self-organizing systems are studied and investigated. Result Emergence is one of the issues that has attracted the attention of researchers these days. In this paper, concerning nine research questions, 180 research papers are studied. In addition to exploring definitions and features of emergence, a variety of research interests has been found, including studies on why and how to identify, measure, validate, predict, model, simulate, and control emergence. Conclusion This study shows that much research had been done not only in computer science but also in other sciences on emergence. In addition to a need to provide new methods, based on various technologies, for identifying, measuring, verifying, modeling, simulating, predicting, and controlling emergence in future research, there is a lack of work regarding many issues on emergence.
{"title":"Emergence phenomena in self-organizing systems: a systematic literature review of concepts, researches, and future prospects","authors":"Somayeh Kalantari, E. Nazemi, B. Masoumi","doi":"10.1080/10919392.2020.1748977","DOIUrl":"https://doi.org/10.1080/10919392.2020.1748977","url":null,"abstract":"ABSTRACT Context Today, we are facing the growing development of distributed systems which their vast scale has challenged their centralized management. Therefore, many researchers design these systems as self-organizing. After implementing self-organizing systems, new behaviors known as emergence form at a global level of the system. Objective The purpose of this paper is to study the concept of emergence in various natural and artificial systems, categorize research activities, identify research pathways of emergence in computer science, and shed light on future research directions. Method In this paper, for a systematic literature review, numerous articles regarding emergence phenomena in self-organizing systems are studied and investigated. Result Emergence is one of the issues that has attracted the attention of researchers these days. In this paper, concerning nine research questions, 180 research papers are studied. In addition to exploring definitions and features of emergence, a variety of research interests has been found, including studies on why and how to identify, measure, validate, predict, model, simulate, and control emergence. Conclusion This study shows that much research had been done not only in computer science but also in other sciences on emergence. In addition to a need to provide new methods, based on various technologies, for identifying, measuring, verifying, modeling, simulating, predicting, and controlling emergence in future research, there is a lack of work regarding many issues on emergence.","PeriodicalId":54777,"journal":{"name":"Journal of Organizational Computing and Electronic Commerce","volume":"30 1","pages":"224 - 265"},"PeriodicalIF":2.9,"publicationDate":"2020-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/10919392.2020.1748977","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46867373","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}
Pub Date : 2020-05-13DOI: 10.1080/10919392.2020.1761750
Fenfen Jiang, Shue Mei, Weijun Zhong
ABSTRACT With the popularity of social media, firms are prone to relying on the existing customers’ social contacts to acquire new customers. Referral reward programs (RRPs) have become one of the most effective methods. We highlight social motives for customer referrals and assume that the customer can obtain both firm-offered rewards and psychological intangible rewards named social value from his successful referral. Then we explore the impact of social value on firms’ optimal referral reward structure by comparing the equilibriums of two nested Stackelberg games among a firm, a sender (existing customer), and a receiver (new customer). One of the games ignores the sender’s social value, while the other one considers the impact of the sender’s social value. Firstly, we give the applicable conditions for using RRPs, and show that the sender’s social value helps the firm avoid excessive rewards by sharing the rewards burden. We also find that the firm’s optimal reward structure shifts away from rewarding the sender toward rewarding the receiver or forsaking the reward programs when the firm takes the sender’s social value into account. Considering the conditions under which the firm should use reward programs, the optimal reward structure is closely related to the tie-strength between the two customers. Concretely, when the tie-strength is weak, the firm tends to reward the sender more; conversely, the firm tends to reward the receiver more.
{"title":"Impact of Customer’s Social Value on Optimizing Referral Reward Programs","authors":"Fenfen Jiang, Shue Mei, Weijun Zhong","doi":"10.1080/10919392.2020.1761750","DOIUrl":"https://doi.org/10.1080/10919392.2020.1761750","url":null,"abstract":"ABSTRACT With the popularity of social media, firms are prone to relying on the existing customers’ social contacts to acquire new customers. Referral reward programs (RRPs) have become one of the most effective methods. We highlight social motives for customer referrals and assume that the customer can obtain both firm-offered rewards and psychological intangible rewards named social value from his successful referral. Then we explore the impact of social value on firms’ optimal referral reward structure by comparing the equilibriums of two nested Stackelberg games among a firm, a sender (existing customer), and a receiver (new customer). One of the games ignores the sender’s social value, while the other one considers the impact of the sender’s social value. Firstly, we give the applicable conditions for using RRPs, and show that the sender’s social value helps the firm avoid excessive rewards by sharing the rewards burden. We also find that the firm’s optimal reward structure shifts away from rewarding the sender toward rewarding the receiver or forsaking the reward programs when the firm takes the sender’s social value into account. Considering the conditions under which the firm should use reward programs, the optimal reward structure is closely related to the tie-strength between the two customers. Concretely, when the tie-strength is weak, the firm tends to reward the sender more; conversely, the firm tends to reward the receiver more.","PeriodicalId":54777,"journal":{"name":"Journal of Organizational Computing and Electronic Commerce","volume":"30 1","pages":"279 - 295"},"PeriodicalIF":2.9,"publicationDate":"2020-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/10919392.2020.1761750","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44563203","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}
Pub Date : 2020-04-14DOI: 10.1080/10919392.2020.1750932
Michal Levi-Bliech, N. Pliskin, L. Fink
ABSTRACT Implementing a mobile application (app) to facilitate electronic commerce and to enhance interaction with customers is quite common in contemporary organizations, and research has shed light on the business value of implementing such apps. However, only few empirical studies have explored the business value of implementing an app that supports, rather than substitutes, face-to-face interaction with customers. This study empirically explores and documents the impact of implementing a sales support app that complements face-to-face interaction of a salesperson with a customer in the process of purchasing a new car. Two consecutive periods were compared, before (conventional process) and after (innovative process) app implementation. The results confirmed that the sales support app added business value to the implementing organization via increased visits (although virtual rather than physical) and car purchases. Yet, app visits increased relatively more than purchases did, resulting in an expected decrease in conversion rate.
{"title":"Implementing A Sales Support app to Complement Face-to-Face Interaction: An Empirical Investigation of Business Value","authors":"Michal Levi-Bliech, N. Pliskin, L. Fink","doi":"10.1080/10919392.2020.1750932","DOIUrl":"https://doi.org/10.1080/10919392.2020.1750932","url":null,"abstract":"ABSTRACT Implementing a mobile application (app) to facilitate electronic commerce and to enhance interaction with customers is quite common in contemporary organizations, and research has shed light on the business value of implementing such apps. However, only few empirical studies have explored the business value of implementing an app that supports, rather than substitutes, face-to-face interaction with customers. This study empirically explores and documents the impact of implementing a sales support app that complements face-to-face interaction of a salesperson with a customer in the process of purchasing a new car. Two consecutive periods were compared, before (conventional process) and after (innovative process) app implementation. The results confirmed that the sales support app added business value to the implementing organization via increased visits (although virtual rather than physical) and car purchases. Yet, app visits increased relatively more than purchases did, resulting in an expected decrease in conversion rate.","PeriodicalId":54777,"journal":{"name":"Journal of Organizational Computing and Electronic Commerce","volume":"30 1","pages":"266 - 278"},"PeriodicalIF":2.9,"publicationDate":"2020-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/10919392.2020.1750932","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41749266","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}
Pub Date : 2020-04-09DOI: 10.1080/10919392.2020.1742552
Xiaodong Qian, Min Li
ABSTRACT In order to measure the similarity of non-equal length and non-numerical sequence effectively, in this paper, the access sequence similarity calculation method was proposed based on the characteristics of e-commerce user access sequence. The sliding window method was improved by increasing the similarity calculation of nodes and optimizing the sliding similarity calculation method. The key factor of Edit Distance on Real Sequences was optimized. It mainly includes the calculation method of increasing the similarity of nodes and optimizing the calculation method of sliding similarity; the calculation method of subcost in the editing distance of real sequences is optimized. Then, the optimized Edit Distance on Real Sequences was embedded into the improved sliding window method to replace the original distance calculation method. Based on the access sequence similarity calculation results, the clustering algorithm was used to get the e-commerce users type. The experimental results showed the following facts: The improved access sequence similarity algorithm can measure the similarity of non-numerical and non-equal length sequences more accurately; based on the similarity of access sequences, it is possible to divide the types of e-commerce users more effectively, besides the e-commerce users are mainly composed of young men, users’ online time shows obvious fragmentation characteristics, their online browsing behavior obeys long tail distribution, they still primarily buy hot items, and the e-commerce users can be divided into six categories.
{"title":"E-Commerce User Type Recognition Based on Access Sequence Similarity","authors":"Xiaodong Qian, Min Li","doi":"10.1080/10919392.2020.1742552","DOIUrl":"https://doi.org/10.1080/10919392.2020.1742552","url":null,"abstract":"ABSTRACT In order to measure the similarity of non-equal length and non-numerical sequence effectively, in this paper, the access sequence similarity calculation method was proposed based on the characteristics of e-commerce user access sequence. The sliding window method was improved by increasing the similarity calculation of nodes and optimizing the sliding similarity calculation method. The key factor of Edit Distance on Real Sequences was optimized. It mainly includes the calculation method of increasing the similarity of nodes and optimizing the calculation method of sliding similarity; the calculation method of subcost in the editing distance of real sequences is optimized. Then, the optimized Edit Distance on Real Sequences was embedded into the improved sliding window method to replace the original distance calculation method. Based on the access sequence similarity calculation results, the clustering algorithm was used to get the e-commerce users type. The experimental results showed the following facts: The improved access sequence similarity algorithm can measure the similarity of non-numerical and non-equal length sequences more accurately; based on the similarity of access sequences, it is possible to divide the types of e-commerce users more effectively, besides the e-commerce users are mainly composed of young men, users’ online time shows obvious fragmentation characteristics, their online browsing behavior obeys long tail distribution, they still primarily buy hot items, and the e-commerce users can be divided into six categories.","PeriodicalId":54777,"journal":{"name":"Journal of Organizational Computing and Electronic Commerce","volume":"30 1","pages":"209 - 223"},"PeriodicalIF":2.9,"publicationDate":"2020-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/10919392.2020.1742552","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48850341","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}
Pub Date : 2020-03-22DOI: 10.1080/10919392.2020.1739395
J. Prodanova, Sonia San Martín Gutiérrez, Nadia H. Jiménez
ABSTRACT Despite its widespread use as a purchase channel, the Internet still provokes consumer concerns when it comes to the acquisition of high-involvement services, such as travel. This study, therefore, explores customers’ intentions to repeat their online travel purchases, depending on the level of attachment they develop with a website, as is driven by high- and low-task relevant website characteristics. With an innovative, electronic Stimulus–Organism–Response model that introduces a new site attachment variable, this study reveals that, among experienced online travel purchasers, service quality, security and privacy issues, and entertainment all function as stimuli to incite affective, cognitive, and social activity and thereby enhance site attachment. This site attachment, in turn, evokes beneficial customers’ responses, in the form of increased intentions to purchase travel services online again. With this distinctive approach to observing customers’ reactions to and interaction with websites, this study establishes several strategic implications that can help companies enhance their service features and provision, as well as ensure lasting relationships with their customers.
{"title":"Achieving customers’ repurchase intention through stimuli and site attachment","authors":"J. Prodanova, Sonia San Martín Gutiérrez, Nadia H. Jiménez","doi":"10.1080/10919392.2020.1739395","DOIUrl":"https://doi.org/10.1080/10919392.2020.1739395","url":null,"abstract":"ABSTRACT Despite its widespread use as a purchase channel, the Internet still provokes consumer concerns when it comes to the acquisition of high-involvement services, such as travel. This study, therefore, explores customers’ intentions to repeat their online travel purchases, depending on the level of attachment they develop with a website, as is driven by high- and low-task relevant website characteristics. With an innovative, electronic Stimulus–Organism–Response model that introduces a new site attachment variable, this study reveals that, among experienced online travel purchasers, service quality, security and privacy issues, and entertainment all function as stimuli to incite affective, cognitive, and social activity and thereby enhance site attachment. This site attachment, in turn, evokes beneficial customers’ responses, in the form of increased intentions to purchase travel services online again. With this distinctive approach to observing customers’ reactions to and interaction with websites, this study establishes several strategic implications that can help companies enhance their service features and provision, as well as ensure lasting relationships with their customers.","PeriodicalId":54777,"journal":{"name":"Journal of Organizational Computing and Electronic Commerce","volume":"30 1","pages":"187 - 208"},"PeriodicalIF":2.9,"publicationDate":"2020-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/10919392.2020.1739395","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43817461","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}
Pub Date : 2020-03-16DOI: 10.1080/10919392.2020.1736466
Yingqiu Zhu, Danyang Huang, W. Xu, Bo Zhang
ABSTRACT Link prediction is one of the most important personalized services in social network platforms. The key point is to predict the probability of the existence of a link between two nodes based on various information in the network. This article combines information of the network structure with the user-generated contents. We propose link prediction indices based on both network structure and topic distribution (NSTD). In contrast to previous literatures, this approach makes full use of the network characteristics, such as homophily, transitivity, clustering, and degree heterogeneity. And we combine these characteristics with topic similarity when constructing indices based on both directly and indirectly connected nodes. Experiment results demonstrate that the proposed method outperforms the previous methods.
{"title":"Link prediction combining network structure and topic distribution in large-scale directed network","authors":"Yingqiu Zhu, Danyang Huang, W. Xu, Bo Zhang","doi":"10.1080/10919392.2020.1736466","DOIUrl":"https://doi.org/10.1080/10919392.2020.1736466","url":null,"abstract":"ABSTRACT Link prediction is one of the most important personalized services in social network platforms. The key point is to predict the probability of the existence of a link between two nodes based on various information in the network. This article combines information of the network structure with the user-generated contents. We propose link prediction indices based on both network structure and topic distribution (NSTD). In contrast to previous literatures, this approach makes full use of the network characteristics, such as homophily, transitivity, clustering, and degree heterogeneity. And we combine these characteristics with topic similarity when constructing indices based on both directly and indirectly connected nodes. Experiment results demonstrate that the proposed method outperforms the previous methods.","PeriodicalId":54777,"journal":{"name":"Journal of Organizational Computing and Electronic Commerce","volume":"30 1","pages":"169 - 185"},"PeriodicalIF":2.9,"publicationDate":"2020-03-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/10919392.2020.1736466","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"59759027","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}
Pub Date : 2020-03-12DOI: 10.1080/10919392.2020.1738203
Nicholas H. Roberts, Jennifer E. Gerow
ABSTRACT We investigate whether the information technology (IT) function’s competence and role affect organizational ambidexterity. We first hypothesize that IT function competence is positively related to organizational ambidexterity. Following this, we suggest that the role of the IT function moderates the aforementioned relationship. We test our hypotheses with a matched pair sample of business managers and IT managers. Our results show that IT function competence positively influences organizational ambidexterity. Furthermore, this relationship is stronger when the IT function aims to be an active business partner or aims to reduce architectural complexity. Our study contributes to research on the IT function and IT value.
{"title":"Connecting the Role of the Information Technology Function to its Contribution to the Organization","authors":"Nicholas H. Roberts, Jennifer E. Gerow","doi":"10.1080/10919392.2020.1738203","DOIUrl":"https://doi.org/10.1080/10919392.2020.1738203","url":null,"abstract":"ABSTRACT We investigate whether the information technology (IT) function’s competence and role affect organizational ambidexterity. We first hypothesize that IT function competence is positively related to organizational ambidexterity. Following this, we suggest that the role of the IT function moderates the aforementioned relationship. We test our hypotheses with a matched pair sample of business managers and IT managers. Our results show that IT function competence positively influences organizational ambidexterity. Furthermore, this relationship is stronger when the IT function aims to be an active business partner or aims to reduce architectural complexity. Our study contributes to research on the IT function and IT value.","PeriodicalId":54777,"journal":{"name":"Journal of Organizational Computing and Electronic Commerce","volume":"30 1","pages":"150 - 168"},"PeriodicalIF":2.9,"publicationDate":"2020-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/10919392.2020.1738203","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45580418","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}
Pub Date : 2020-02-18DOI: 10.1080/10919392.2020.1723957
Dave Chatterjee
{"title":"Bringing the Best Actionable Insights on Cybersecurity: A Call for Papers","authors":"Dave Chatterjee","doi":"10.1080/10919392.2020.1723957","DOIUrl":"https://doi.org/10.1080/10919392.2020.1723957","url":null,"abstract":"","PeriodicalId":54777,"journal":{"name":"Journal of Organizational Computing and Electronic Commerce","volume":"31 1","pages":"383 - 385"},"PeriodicalIF":2.9,"publicationDate":"2020-02-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42026896","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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