Pub Date : 2022-01-26DOI: 10.1108/imds-09-2020-0562
Liangyan Liu, Ming Cheng
PurposeIn the process of building the “Belt and Road” and “Bright Road” community of interests between China and Kazakhstan, this paper proposes the construction of an inland nuclear power plant in Kazakhstan. Considering the uncertainty of investment in nuclear power generation, the authors propose the MGT (Monte-Carlo and Gaussian Radial Basis with Tensor factorization) utility evaluation model to evaluate the risk of investment in nuclear power in Kazakhstan and provide a relevant reference for decision making on inland nuclear investment in Kazakhstan.Design/methodology/approachBased on real options portfolio combined with a weighted utility function, this study takes into account the uncertainties associated with nuclear power investments through a minimum variance Monte Carlo approach, proposes a noise-enhancing process combined with geometric Brownian motion in solving complex conditions, and incorporates a measure of investment flexibility and strategic value in the investment, and then uses a deep noise reduction encoder to learn the initial values for potential features of cost and investment effectiveness. A Gaussian radial basis function used to construct a weighted utility function for each uncertainty, generate a minimization of the objective function for the tensor decomposition, and then optimize the objective loss function for the tensor decomposition, find the corresponding weights, and perform noise reduction to generalize the nonlinear problem to evaluate the effectiveness of nuclear power investment. Finally, the two dimensions of cost and risk (estimation of investment value and measurement of investment risk) are applied and simulated through actual data in Kazakhstan.FindingsThe authors assess the core indicators of Kazakhstan's nuclear power plants throughout their construction and operating cycles, based on data relating to a cluster of nuclear power plants of 10 different technologies. The authors compared it with several popular methods for evaluating the benefits of nuclear power generation and conducted subsequent sensitivity analyses of key indicators. Experimental results on the dataset show that the MGT method outperforms the other four methods and that changes in nuclear investment returns are more sensitive to changes in costs while operating cash flows from nuclear power are certainly an effective way to drive investment reform in inland nuclear power generation in Kazakhstan at current levels of investment costs.Research limitations/implicationsFuture research could consider exploring other excellent methods to improve the accuracy of the investment prediction further using sparseness and noise interference. Also consider collecting some expert advice and providing more appropriate specific suggestions, which will facilitate the application in practice.Practical implicationsThe Novel Coronavirus epidemic has plunged the global economy into a deep recession, the tension between China and the US has made the ene
目的在构建中哈“一带一路”和“光明之路”利益共同体的过程中，本文提出在哈萨克斯坦建设一座内陆核电站。考虑到核电投资的不确定性，作者提出了MGT（Monte Carlo and Gaussian Radial Basis with Tensor Factorion）效用评估模型来评估哈萨克斯坦核电投资的风险，并为哈萨克斯坦内陆核电投资决策提供了相关参考，本研究通过最小方差蒙特卡罗方法考虑了与核电投资相关的不确定性，提出了一种结合几何布朗运动求解复杂条件的噪声增强过程，并在投资中纳入了投资灵活性和战略价值的衡量标准，然后使用深度降噪编码器来学习成本和投资有效性的潜在特征的初始值。高斯径向基函数用于为每个不确定性构造加权效用函数，生成张量分解的目标函数的最小化，然后优化张量分解的目的损失函数，找到相应的权重，并通过降噪来推广非线性问题，以评估核电投资的有效性。最后，通过哈萨克斯坦的实际数据，应用和模拟了成本和风险两个维度（投资价值的估计和投资风险的衡量）。作者将其与几种常用的评估核能发电效益的方法进行了比较，并随后对关键指标进行了敏感性分析。数据集上的实验结果表明，MGT方法优于其他四种方法，核投资回报的变化对成本的变化更敏感，而在当前投资成本水平下，核电运营现金流无疑是推动哈萨克斯坦内陆核电投资改革的有效途径。研究局限性/含义未来的研究可以考虑探索其他优秀的方法，进一步利用稀疏性和噪声干扰来提高投资预测的准确性。还可以考虑收集一些专家建议，并提供更合适的具体建议，这将有助于在实践中应用。现实含义新型冠状病毒疫情使全球经济陷入深度衰退，中美紧张关系使能源合作之路异常曲折，哈萨克斯坦在中亚具有天然的地理和资源优势，因此中哈能源合作成为新的机遇期，为中国政治经济稳定提供了有力保障。结合哈萨克斯坦建设区域性国际能源基地的发展战略，提出了在巴尔喀什和阿克套建设大型核电站的基本思路。这项工作对核能发电的投资将是一个很好的启示。独创性/价值本研究将蒙特卡洛模拟与复杂条件下的几何布朗运动相结合，解决了噪声增加的问题，增加了投资灵活性和战略价值的衡量标准，构造了基于高斯径向基函数的降噪权重效用函数，并将非线性问题推广到核电投资效益评价中。
{"title":"Benefit and risk evaluation of inland nuclear generation investment in Kazakhstan combined with an analytical MGT method","authors":"Liangyan Liu, Ming Cheng","doi":"10.1108/imds-09-2020-0562","DOIUrl":"https://doi.org/10.1108/imds-09-2020-0562","url":null,"abstract":"PurposeIn the process of building the “Belt and Road” and “Bright Road” community of interests between China and Kazakhstan, this paper proposes the construction of an inland nuclear power plant in Kazakhstan. Considering the uncertainty of investment in nuclear power generation, the authors propose the MGT (Monte-Carlo and Gaussian Radial Basis with Tensor factorization) utility evaluation model to evaluate the risk of investment in nuclear power in Kazakhstan and provide a relevant reference for decision making on inland nuclear investment in Kazakhstan.Design/methodology/approachBased on real options portfolio combined with a weighted utility function, this study takes into account the uncertainties associated with nuclear power investments through a minimum variance Monte Carlo approach, proposes a noise-enhancing process combined with geometric Brownian motion in solving complex conditions, and incorporates a measure of investment flexibility and strategic value in the investment, and then uses a deep noise reduction encoder to learn the initial values for potential features of cost and investment effectiveness. A Gaussian radial basis function used to construct a weighted utility function for each uncertainty, generate a minimization of the objective function for the tensor decomposition, and then optimize the objective loss function for the tensor decomposition, find the corresponding weights, and perform noise reduction to generalize the nonlinear problem to evaluate the effectiveness of nuclear power investment. Finally, the two dimensions of cost and risk (estimation of investment value and measurement of investment risk) are applied and simulated through actual data in Kazakhstan.FindingsThe authors assess the core indicators of Kazakhstan's nuclear power plants throughout their construction and operating cycles, based on data relating to a cluster of nuclear power plants of 10 different technologies. The authors compared it with several popular methods for evaluating the benefits of nuclear power generation and conducted subsequent sensitivity analyses of key indicators. Experimental results on the dataset show that the MGT method outperforms the other four methods and that changes in nuclear investment returns are more sensitive to changes in costs while operating cash flows from nuclear power are certainly an effective way to drive investment reform in inland nuclear power generation in Kazakhstan at current levels of investment costs.Research limitations/implicationsFuture research could consider exploring other excellent methods to improve the accuracy of the investment prediction further using sparseness and noise interference. Also consider collecting some expert advice and providing more appropriate specific suggestions, which will facilitate the application in practice.Practical implicationsThe Novel Coronavirus epidemic has plunged the global economy into a deep recession, the tension between China and the US has made the ene","PeriodicalId":51064,"journal":{"name":"Industrial Management & Data Systems","volume":"1 1","pages":""},"PeriodicalIF":5.5,"publicationDate":"2022-01-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46887094","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-09-15DOI: 10.1108/imds-02-2021-0093
Richard N. Rutter, S. Barnes, S. Roper, J. Nadeau, F. Lettice
PurposeThis research tests empirically the level of consumer engagement with a product via a nonbrand-controlled platform. The authors explore how social media influencers and traditional celebrities are using products within their own social media Instagram posts and how well their perceived endorsement of that product engages their network of followers.Design/methodology/approachA total of 226,881 posts on Instagram were analyzed using the Inception V3 convolutional neural network (CNN) pre-trained on the ImageNet dataset to identify product placement within the Instagram images of 75 of the world's most important social media influencers. The data were used to empirically test the relationships between influencers, product placement and network engagement and efficiency.FindingsInfluencers achieved higher network engagement efficiencies than celebrities; however, celebrity reach was important for engagement overall. Specialty influencers, known for their “subject” expertise, achieved better network engagement efficiency for related product categories. The highest level of engagement efficiency was achieved by beauty influencers advocating and promoting cosmetic and beauty products.Practical implicationsTo maximize engagement and return on investment, manufacturers, retailers and brands must ensure a close fit between the product type and category of influencer promoting a product within their social media posts.Originality/valueMost research to date has focused on brand-controlled social media accounts. This study focused on traditional celebrities and social media influencers and product placement within their own Instagram posts to extend understanding of the perception of endorsement and subsequent engagement with followers. The authors extend the theory of network effects to reflect the complexity inherent in the context of social media influencers.
{"title":"Social media influencers, product placement and network engagement: using AI image analysis to empirically test relationships","authors":"Richard N. Rutter, S. Barnes, S. Roper, J. Nadeau, F. Lettice","doi":"10.1108/imds-02-2021-0093","DOIUrl":"https://doi.org/10.1108/imds-02-2021-0093","url":null,"abstract":"PurposeThis research tests empirically the level of consumer engagement with a product via a nonbrand-controlled platform. The authors explore how social media influencers and traditional celebrities are using products within their own social media Instagram posts and how well their perceived endorsement of that product engages their network of followers.Design/methodology/approachA total of 226,881 posts on Instagram were analyzed using the Inception V3 convolutional neural network (CNN) pre-trained on the ImageNet dataset to identify product placement within the Instagram images of 75 of the world's most important social media influencers. The data were used to empirically test the relationships between influencers, product placement and network engagement and efficiency.FindingsInfluencers achieved higher network engagement efficiencies than celebrities; however, celebrity reach was important for engagement overall. Specialty influencers, known for their “subject” expertise, achieved better network engagement efficiency for related product categories. The highest level of engagement efficiency was achieved by beauty influencers advocating and promoting cosmetic and beauty products.Practical implicationsTo maximize engagement and return on investment, manufacturers, retailers and brands must ensure a close fit between the product type and category of influencer promoting a product within their social media posts.Originality/valueMost research to date has focused on brand-controlled social media accounts. This study focused on traditional celebrities and social media influencers and product placement within their own Instagram posts to extend understanding of the perception of endorsement and subsequent engagement with followers. The authors extend the theory of network effects to reflect the complexity inherent in the context of social media influencers.","PeriodicalId":51064,"journal":{"name":"Industrial Management & Data Systems","volume":"121 1","pages":"2387-2410"},"PeriodicalIF":5.5,"publicationDate":"2021-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"62045530","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-08-24DOI: 10.1108/imds-12-2020-0756
Anders Haug
PurposeNumerous data quality (DQ) definitions in the form of sets of DQ dimensions are found in the literature. The great differences across such DQ classifications (DQCs) imply a lack of clarity about what DQ is. For an improved foundation for future research, this paper aims to clarify the ways in which DQCs differ and provide guidelines for dealing with this variance.Design/methodology/approachA literature review identifies DQCs in conference and journal articles, which are analyzed to reveal the types of differences across these. On this basis, guidelines for future research are developed.FindingsThe literature review found 110 unique DQCs in journals and conference articles. The analysis of these articles identified seven distinct types of differences across DQCs. This gave rise to the development of seven guidelines for future DQ research.Research limitations/implicationsBy identifying differences across DQCs and providing a set of guidelines, this paper may promote that future research, to a greater extent, will converge around common understandings of DQ.Practical implicationsAwareness of the identified types of differences across DQCs may support managers when planning and conducting DQ improvement projects.Originality/valueThe literature review did not identify articles, which, based on systematic searches, identify and analyze existing DQCs. Thus, this paper provides new knowledge on the variance across DQCs, as well as guidelines for addressing this.
{"title":"Understanding the differences across data quality classifications: a literature review and guidelines for future research","authors":"Anders Haug","doi":"10.1108/imds-12-2020-0756","DOIUrl":"https://doi.org/10.1108/imds-12-2020-0756","url":null,"abstract":"PurposeNumerous data quality (DQ) definitions in the form of sets of DQ dimensions are found in the literature. The great differences across such DQ classifications (DQCs) imply a lack of clarity about what DQ is. For an improved foundation for future research, this paper aims to clarify the ways in which DQCs differ and provide guidelines for dealing with this variance.Design/methodology/approachA literature review identifies DQCs in conference and journal articles, which are analyzed to reveal the types of differences across these. On this basis, guidelines for future research are developed.FindingsThe literature review found 110 unique DQCs in journals and conference articles. The analysis of these articles identified seven distinct types of differences across DQCs. This gave rise to the development of seven guidelines for future DQ research.Research limitations/implicationsBy identifying differences across DQCs and providing a set of guidelines, this paper may promote that future research, to a greater extent, will converge around common understandings of DQ.Practical implicationsAwareness of the identified types of differences across DQCs may support managers when planning and conducting DQ improvement projects.Originality/valueThe literature review did not identify articles, which, based on systematic searches, identify and analyze existing DQCs. Thus, this paper provides new knowledge on the variance across DQCs, as well as guidelines for addressing this.","PeriodicalId":51064,"journal":{"name":"Industrial Management & Data Systems","volume":"121 1","pages":"2651-2671"},"PeriodicalIF":5.5,"publicationDate":"2021-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"62045674","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-08-23DOI: 10.1108/imds-09-2020-0550
Shang-Yu Chen, Qingfei Min, Xuefei Xu
PurposeAs social commerce migrates to the mobile platform, mobile social commerce (ms–commerce), an emerging way of conducting social commerce in the mobile environment, is gaining popularity among mobile users. Although impulse buying in social commerce has been the focus of scholars in recent years, individuals' impulse-buying behavior in ms–commerce has not been highlighted and therefore is worth investigating. This study addressed that gap by differentiating and monitoring the impacts that three key targets of social identification in ms–commerce exerted on impulse buying. Furthermore, previous studies had highlighted the importance of culture in impulse buying in other contexts, so the authors examined how the effects of the key identification targets differed across cultures, as a result of cultural diversity among the ms–commerce users. Finally, the authors drew upon the lens of information technology (IT) affordances to explore how different combinations of ms–commerce affordances influenced each target of identification.Design/methodology/approachThis research first applied a qualitative methodology by using semi-structured interviews with 27 ms–commerce users to extract the relevant subdimensions of IT affordances in ms–commerce. Then, the authors tested their hypotheses with survey data collected from the United States and China.FindingsThe results clearly illustrate that three key targets of social identification had varying impacts on impulse buying in different cultural dimensions. In addition, nearly all of the proposed IT affordances in ms–commerce aided users in building multiple identifications, to various degrees.Originality/valueThis study extends social commerce research by examining the important role that social identification plays in impulse buying in the mobile environment. Moreover, unlike previous studies that mainly had focused on ordinary buying in social commerce across cultures, this study investigated the relative importance of the targets of social identification on impulse buying in different espoused cultural dimensions. Importantly, the authors used a technology affordance lens to also uncover the context-specific stimulators of separate identification targets, thus going beyond the existing body of knowledge that focused on general beliefs.
随着社交商务向移动平台迁移，移动社交商务(mobile social commerce, ms-commerce)作为一种在移动环境下进行社交商务的新兴方式，越来越受到移动用户的欢迎。虽然近年来社交商务中的冲动购买一直是学者们关注的焦点，但个人在电子商务中的冲动购买行为并没有得到重视，因此值得研究。本研究通过区分和监测电子商务中社会认同的三个关键目标对冲动购买的影响来解决这一差距。此外，之前的研究强调了文化在其他情况下冲动购买中的重要性，因此作者研究了不同文化背景下关键识别目标的影响是如何不同的，这是电子商务用户文化多样性的结果。最后，作者利用信息技术(IT)功能的视角来探讨不同的电子商务功能组合如何影响每个识别目标。设计/方法/方法本研究首先采用定性方法，对27名电子商务用户进行半结构化访谈，提取电子商务中IT支持的相关子维度。然后，作者用从美国和中国收集的调查数据验证了他们的假设。研究结果清楚地表明，社会认同的三个关键目标在不同的文化维度上对冲动购买有不同的影响。此外，几乎所有建议的电子商务IT功能都在不同程度上帮助用户构建多个标识。原创性/价值本研究通过考察社会认同在移动环境下冲动购买中所起的重要作用，扩展了社交商务研究。此外，与以往的研究主要关注跨文化社交商务中的普通购买不同，本研究调查了不同文化维度下社会认同目标对冲动购买的相对重要性。重要的是，作者还使用了技术支持透镜来揭示单独识别目标的特定情境刺激因素，从而超越了现有的专注于一般信念的知识体系。
{"title":"Investigating the role of social identification on impulse buying in mobile social commerce: a cross-cultural comparison","authors":"Shang-Yu Chen, Qingfei Min, Xuefei Xu","doi":"10.1108/imds-09-2020-0550","DOIUrl":"https://doi.org/10.1108/imds-09-2020-0550","url":null,"abstract":"PurposeAs social commerce migrates to the mobile platform, mobile social commerce (ms–commerce), an emerging way of conducting social commerce in the mobile environment, is gaining popularity among mobile users. Although impulse buying in social commerce has been the focus of scholars in recent years, individuals' impulse-buying behavior in ms–commerce has not been highlighted and therefore is worth investigating. This study addressed that gap by differentiating and monitoring the impacts that three key targets of social identification in ms–commerce exerted on impulse buying. Furthermore, previous studies had highlighted the importance of culture in impulse buying in other contexts, so the authors examined how the effects of the key identification targets differed across cultures, as a result of cultural diversity among the ms–commerce users. Finally, the authors drew upon the lens of information technology (IT) affordances to explore how different combinations of ms–commerce affordances influenced each target of identification.Design/methodology/approachThis research first applied a qualitative methodology by using semi-structured interviews with 27 ms–commerce users to extract the relevant subdimensions of IT affordances in ms–commerce. Then, the authors tested their hypotheses with survey data collected from the United States and China.FindingsThe results clearly illustrate that three key targets of social identification had varying impacts on impulse buying in different cultural dimensions. In addition, nearly all of the proposed IT affordances in ms–commerce aided users in building multiple identifications, to various degrees.Originality/valueThis study extends social commerce research by examining the important role that social identification plays in impulse buying in the mobile environment. Moreover, unlike previous studies that mainly had focused on ordinary buying in social commerce across cultures, this study investigated the relative importance of the targets of social identification on impulse buying in different espoused cultural dimensions. Importantly, the authors used a technology affordance lens to also uncover the context-specific stimulators of separate identification targets, thus going beyond the existing body of knowledge that focused on general beliefs.","PeriodicalId":51064,"journal":{"name":"Industrial Management & Data Systems","volume":"70 1","pages":"2571-2594"},"PeriodicalIF":5.5,"publicationDate":"2021-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"62045583","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-08-18DOI: 10.1108/imds-04-2021-0209
Nastaran Hajiheydari, Mohammad Soltani Delgosha, Yichuan Wang, Hossein Olya
PurposeBig data analytics (BDA) is recognized as a recent breakthrough technology with potential business impact, however, the roadmap for its successful implementation and the path to exploiting its essential value remains unclear. This study aims to provide a deeper understanding of the enablers facilitating BDA implementation in the banking and financial service sector from the perspective of interdependencies and interrelations.Design/methodology/approachWe use an integrated approach that incorporates Delphi study, interpretive structural modelling (ISM) and fuzzy MICMAC methodology to identify the interactions among enablers that determine the success of BDA implementation. Our integrated approach utilizes experts' domain knowledge and gains a novel insight into the underlying causal relations associated with enablers, linguistic evaluation of the mutual impacts among variables and incorporating two innovative ways for visualizing the results.FindingsOur findings highlight the key role of enabling factors, including technical and skilled workforce, financial support, infrastructure readiness and selecting appropriate big data technologies, that have significant driving impacts on other enablers in a hierarchical model. The results provide reliable, robust and easy to understand insights about the dynamics of BDA implementation in banking and financial service as a whole system while demonstrating potential influences of all interconnected influential factors.Originality/valueThis study explores the key enablers leading to successful BDA implementation in the banking and financial service sector. More importantly, it reveals the interrelationships of factors by calculating driving and dependence degrees. This exploration provides managers with a clear strategic path towards effective BDA implementation.
{"title":"Exploring the paths to big data analytics implementation success in banking and financial service: an integrated approach","authors":"Nastaran Hajiheydari, Mohammad Soltani Delgosha, Yichuan Wang, Hossein Olya","doi":"10.1108/imds-04-2021-0209","DOIUrl":"https://doi.org/10.1108/imds-04-2021-0209","url":null,"abstract":"PurposeBig data analytics (BDA) is recognized as a recent breakthrough technology with potential business impact, however, the roadmap for its successful implementation and the path to exploiting its essential value remains unclear. This study aims to provide a deeper understanding of the enablers facilitating BDA implementation in the banking and financial service sector from the perspective of interdependencies and interrelations.Design/methodology/approachWe use an integrated approach that incorporates Delphi study, interpretive structural modelling (ISM) and fuzzy MICMAC methodology to identify the interactions among enablers that determine the success of BDA implementation. Our integrated approach utilizes experts' domain knowledge and gains a novel insight into the underlying causal relations associated with enablers, linguistic evaluation of the mutual impacts among variables and incorporating two innovative ways for visualizing the results.FindingsOur findings highlight the key role of enabling factors, including technical and skilled workforce, financial support, infrastructure readiness and selecting appropriate big data technologies, that have significant driving impacts on other enablers in a hierarchical model. The results provide reliable, robust and easy to understand insights about the dynamics of BDA implementation in banking and financial service as a whole system while demonstrating potential influences of all interconnected influential factors.Originality/valueThis study explores the key enablers leading to successful BDA implementation in the banking and financial service sector. More importantly, it reveals the interrelationships of factors by calculating driving and dependence degrees. This exploration provides managers with a clear strategic path towards effective BDA implementation.","PeriodicalId":51064,"journal":{"name":"Industrial Management & Data Systems","volume":"121 1","pages":"2498-2529"},"PeriodicalIF":5.5,"publicationDate":"2021-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"62045569","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-08-17DOI: 10.1108/imds-12-2020-0712
Zhongjun Tang, Bo-Feng He
PurposeThe purpose of this paper is to explore how the number and quality of games that publishers have released, popularity of game genre, age rating and package size are configured to determine the mobile game takeoff in a short time.Design/methodology/approachBased on the signaling theory, the authors present a conceptual model. Using actual data about 170 mobile games at their initial stage in the Apple App store, the authors test the conceptual model by applying fuzzy qualitative comparative analysis (fsQCA).FindingsThe findings identify four solutions that explain Mobile game takeoff in a short time. The authors highlight the role of the number and quality of games released by publishers, as well as that of popular game genres, which are always core factors when present.Originality/valueThis paper complements the previous research on the diffusion of mobile games by exploring which information combinations can lead to mobile games takeoff in a short time from the perspective of configuration. FsQCA serves as a better tool for explaining the complex relationships among variables than a regression analysis approach does. The authors extend existing knowledge on how the number and quality of games that publishers have released, popularity of game genre, age rating and package size combine to lead to takeoff of mobile games in a short time.
{"title":"Explaining mobile game takeoff through information configuration","authors":"Zhongjun Tang, Bo-Feng He","doi":"10.1108/imds-12-2020-0712","DOIUrl":"https://doi.org/10.1108/imds-12-2020-0712","url":null,"abstract":"PurposeThe purpose of this paper is to explore how the number and quality of games that publishers have released, popularity of game genre, age rating and package size are configured to determine the mobile game takeoff in a short time.Design/methodology/approachBased on the signaling theory, the authors present a conceptual model. Using actual data about 170 mobile games at their initial stage in the Apple App store, the authors test the conceptual model by applying fuzzy qualitative comparative analysis (fsQCA).FindingsThe findings identify four solutions that explain Mobile game takeoff in a short time. The authors highlight the role of the number and quality of games released by publishers, as well as that of popular game genres, which are always core factors when present.Originality/valueThis paper complements the previous research on the diffusion of mobile games by exploring which information combinations can lead to mobile games takeoff in a short time from the perspective of configuration. FsQCA serves as a better tool for explaining the complex relationships among variables than a regression analysis approach does. The authors extend existing knowledge on how the number and quality of games that publishers have released, popularity of game genre, age rating and package size combine to lead to takeoff of mobile games in a short time.","PeriodicalId":51064,"journal":{"name":"Industrial Management & Data Systems","volume":"121 1","pages":"2411-2425"},"PeriodicalIF":5.5,"publicationDate":"2021-08-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"62045627","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-06-27DOI: 10.1108/IMDS-08-2018-0370
Chang Heon Lee, Yiyang Bian, Rajaa Karaouzene, Nasreen Suleiman
Purpose The purpose of this paper is to explore how linguistic style and message substance influence persuasion in civic crowdfunding marketplaces in which written narrative pitch become a vital communication to attract private contributions to public goods and services. Drawing on the elaboration likelihood model (ELM), the authors operationalize the linguistic style of the narrative pitch as language power and message substance as issue-relevant argument quality. In this paper, the authors examine how characteristics of both style and message are related to the outcome of civic crowdfunded projects. Design/methodology/approach The data on civic crowdfunding projects were retrieved from Spacehive, the platform that dedicated mainly to civic projects ranging from community programs, social-oriented enterprises, to infrastructure or facility development. Each of the narrative samples is analyzed using a computerized text analysis package called the Linguistic Inquiry and Word Count to extract the features of the linguistic style and message substance in the narratives. The logistic regression models are estimated to assess the impact of both linguistic style and message substance on crowdfunding decisions. Findings The results show that funding outcomes can be improved with psychological language dimensions (i.e. positive affective and perceptual language). However, extensive use of social language does not help project creators to increase their chance of funding performance; but instead, such language reduces the likelihood of project success. Additionally, message substance or issue-relevant information such as money and risk language influences funding outcome. Originality/value Very few empirical studies investigated the differential effects of language style and message substance on funding performance of crowdfunding campaigns. The authors draw upon the dual process of persuasion as a theoretical base to identify a comprehensive set of linguistic style and message substance and to examine the role of such features in an emerging civic crowdfunding market. This study advances the application of the dual process in ELM by identifying and examining distinct persuasive cues originating from linguistics styles and message contents.
{"title":"Examining the role of narratives in civic crowdfunding: linguistic style and message substance","authors":"Chang Heon Lee, Yiyang Bian, Rajaa Karaouzene, Nasreen Suleiman","doi":"10.1108/IMDS-08-2018-0370","DOIUrl":"https://doi.org/10.1108/IMDS-08-2018-0370","url":null,"abstract":"\u0000Purpose\u0000The purpose of this paper is to explore how linguistic style and message substance influence persuasion in civic crowdfunding marketplaces in which written narrative pitch become a vital communication to attract private contributions to public goods and services. Drawing on the elaboration likelihood model (ELM), the authors operationalize the linguistic style of the narrative pitch as language power and message substance as issue-relevant argument quality. In this paper, the authors examine how characteristics of both style and message are related to the outcome of civic crowdfunded projects.\u0000\u0000\u0000Design/methodology/approach\u0000The data on civic crowdfunding projects were retrieved from Spacehive, the platform that dedicated mainly to civic projects ranging from community programs, social-oriented enterprises, to infrastructure or facility development. Each of the narrative samples is analyzed using a computerized text analysis package called the Linguistic Inquiry and Word Count to extract the features of the linguistic style and message substance in the narratives. The logistic regression models are estimated to assess the impact of both linguistic style and message substance on crowdfunding decisions.\u0000\u0000\u0000Findings\u0000The results show that funding outcomes can be improved with psychological language dimensions (i.e. positive affective and perceptual language). However, extensive use of social language does not help project creators to increase their chance of funding performance; but instead, such language reduces the likelihood of project success. Additionally, message substance or issue-relevant information such as money and risk language influences funding outcome.\u0000\u0000\u0000Originality/value\u0000Very few empirical studies investigated the differential effects of language style and message substance on funding performance of crowdfunding campaigns. The authors draw upon the dual process of persuasion as a theoretical base to identify a comprehensive set of linguistic style and message substance and to examine the role of such features in an emerging civic crowdfunding market. This study advances the application of the dual process in ELM by identifying and examining distinct persuasive cues originating from linguistics styles and message contents.\u0000","PeriodicalId":51064,"journal":{"name":"Industrial Management & Data Systems","volume":"1 1","pages":""},"PeriodicalIF":5.5,"publicationDate":"2019-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1108/IMDS-08-2018-0370","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42489199","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-08-03DOI: 10.1108/imds-08-2017-0349
Manuel Alonso Dos Santos, Francisco Rejón Guardia, Ferran Calabuig Moreno
Purpose The purpose of this paper is to assess the influences and efficiency of a sports sponsorship in an online brand community. Design/methodology/approach The study was conducted through interviews with 609 social network users of a Spanish first league soccer team. The partial least squares (PLS) methodology was applied with a posteriori segmentation (PLS prediction-oriented segmentation (POS)). Findings The attitude toward the sponsor helps to assess the efficiency of sponsorships between companies. This variable is particularly relevant for evaluating sponsorship efficiency in online brand communities. Improving trust and assessing the sense of membership directly improves attitudes toward the team and the sponsored brands. The attitude toward the sponsor has a direct and positive impact on the purchase intentions. The use of a posteriori segmentation with the PLS–POS technique helps discriminate between groups. Research limitations/implications Among the limitations encountered, further study would require using a sample of various sports disciplines and cultures. Practical implications Specific actions and communication strategies are defined for each segment and in general to adapt communication strategies that improve identification with virtual brand communities. The study has revealed involvement-related differences resulting from the impact that engagement with the sponsored team may have on the assessed relationships. Originality/value The study of the effects of sponsorship and the use of a posteriori variables user segmentation in an online brand community are used.
{"title":"Sponsorship image transfer theory in virtual brand communities","authors":"Manuel Alonso Dos Santos, Francisco Rejón Guardia, Ferran Calabuig Moreno","doi":"10.1108/imds-08-2017-0349","DOIUrl":"https://doi.org/10.1108/imds-08-2017-0349","url":null,"abstract":"\u0000Purpose\u0000The purpose of this paper is to assess the influences and efficiency of a sports sponsorship in an online brand community.\u0000\u0000\u0000Design/methodology/approach\u0000The study was conducted through interviews with 609 social network users of a Spanish first league soccer team. The partial least squares (PLS) methodology was applied with a posteriori segmentation (PLS prediction-oriented segmentation (POS)).\u0000\u0000\u0000Findings\u0000The attitude toward the sponsor helps to assess the efficiency of sponsorships between companies. This variable is particularly relevant for evaluating sponsorship efficiency in online brand communities. Improving trust and assessing the sense of membership directly improves attitudes toward the team and the sponsored brands. The attitude toward the sponsor has a direct and positive impact on the purchase intentions. The use of a posteriori segmentation with the PLS–POS technique helps discriminate between groups.\u0000\u0000\u0000Research limitations/implications\u0000Among the limitations encountered, further study would require using a sample of various sports disciplines and cultures.\u0000\u0000\u0000Practical implications\u0000Specific actions and communication strategies are defined for each segment and in general to adapt communication strategies that improve identification with virtual brand communities. The study has revealed involvement-related differences resulting from the impact that engagement with the sponsored team may have on the assessed relationships.\u0000\u0000\u0000Originality/value\u0000The study of the effects of sponsorship and the use of a posteriori variables user segmentation in an online brand community are used.\u0000","PeriodicalId":51064,"journal":{"name":"Industrial Management & Data Systems","volume":"43 1","pages":""},"PeriodicalIF":5.5,"publicationDate":"2018-08-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86293905","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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