How talent capability can shape service analytics capability in the big data environment?

We know very little about how big data-driven service analytics capabilities (SAC) are built in data-driven service organizations and the potential role of talent capability in facilitating overall SAC and the impact of both on firm performance (FPER). Drawing on the dynamic capabilities (DC) approach, this study investigates the link between SAC and FPER examining the mediating role of talent capability and the moderating influence of a firm’s strategic alignment. On the basis of two Delphi studies and survey data from 267 service analysts in the US and France, the findings show that even though SAC are built on technology, talent and information capabilities, their overall impact on firm performance is mediated by the level of talent capability of service analytics managers. The findings also confirm the critical moderating impact of strategic alignment between dynamic talent capability and firm performance in the big data environment.     

The intermediating role of big data analytics capability between responsive and proactive market orientations and firm performance in the retail industry

Big data analytics capability (BDAC) is the key resource for competitive advantage in the drastically changing market. Although some studies have investigated the impacts on firm performance, there is limited understanding of how firms enhance their BDAC. This study draws on organisational culture and investigates the effects of responsive and proactive market orientations on BDAC and firm performance. The results show that both responsive and proactive market orientations increase BDAC. Further, BDAC fully mediates the relationship between these two market orientations and firm performance. Our findings suggest that BDAC researchers should focus on market orientations that enhance BDAC.     

Big data and predictive analytics for supply chain and organizational performance

Scholars acknowledge the importance of big data and predictive analytics (BDPA) in achieving business value and firm performance. However, the impact of BDPA assimilation on supply chain (SCP) and organizational performance (OP) has not been thoroughly investigated. To address this gap, this paper draws on resource-based view. It conceptualizes assimilation as a three stage process (acceptance, routinization, and assimilation) and identifies the influence of resources (connectivity and information sharing) under the mediation effect of top management commitment on big data assimilation (capability), SCP and OP. The findings suggest that connectivity and information sharing under the mediation effect of top management commitment are positively related to BDPA acceptance, which is positively related to BDPA assimilation under the mediation effect of BDPA routinization, and positively related to SCP and OP. Limitations and future research directions are provided.     

The Effect of Environmental Corporate Social Responsibility on Environmental Performance and Business Competitiveness: The Mediation of Green Information Technology Capital

With the emergence of environmental sustainability and green business management, increasing demands have been made on businesses in the areas of environmental corporate social responsibility (ECSR). Furthermore, the influence of ECSR on green capital investment, environmental performance, and business competitiveness has also been the subject of attention from enterprises. However, in previous studies, the mediating role of green information technology (IT) capital in the relationship between ECSR, environmental performance, and business competitiveness, has not been investigated by researchers. In order to bridge this gap in the ECSR literature, this study aims to examine the influence of ECSR on green IT capital, and the consequent effect of green IT capital on environmental performance and business competitiveness. Data were collected from 358 companies from the top 1000 manufacturers in Taiwan. The results confirmed that ECSR has significant positive effects on green IT human capital, green IT structural capital, and green IT relational capital. Green IT structural capital and green IT relational capital have positive effects on environmental performance and business competitiveness, and environmental performance has a positive effect on business competitiveness. In addition, green IT structural capital and green IT relational capital have partial mediating effects on ECSR, environmental performance, and business competitiveness. The implications and suggestions for future research are discussed.     

知识动态能力视角的电商平台大数据分析价值链战略

电子商务领域信息技术的开放性提高了服务创新的可见性,为适应多维度要素交互的平台竞争环境,需要基于电商平台丰富的数据资源,通过大数据分析提高战略规划的动态性、灵活性和响应敏捷性,形成一种能够快速集合与组织资源的模式,实现业务价值传递的可持续,满足竞争对抗与互动以及时间轴动态演化的需要。鉴于此,基于大数据分析、知识管理、动态能力、业务流程理论和指向性网络调查数据,构建大数据分析价值链战略研究模型,探讨大数据分析、动态能力、流程级创新与核心竞争力及战略绩效之间的关联。研究结果表明,大数据分析能实现有效的内生源和外生源知识管理,帮助企业形成动态能力,构建核心竞争力,进而提高战略绩效;大数据分析能提高企业组织的灵活性,可作为企业在竞争中赖以生存发展的战略投资;外生源知识管理和内生源知识管理均可单独运作产生知识动态能力,但外生源知识管理的作用更显著有效,更值得重视;知识共享是流程级创新的潜在障碍,与合作商进行知识共享需要选择合适的路径;动态能力既可直接影响流程级创新与核心竞争力,也可调节知识资产对竞争力的影响。总之,大数据分析能够通过影响动态能力和流程级创新来提高核心竞争力,且动态能力在知识管理与流程级创新及核心竞争力(战略绩效)间具有中介作用,电商平台应客观认识大数据分析潜在价值,将之纳入信息技术战略,通过梳理大数据分析→动态能力→核心竞争力→战略绩效的价值链过程,形成战略协同,最终提高知识创新的边际绩效。     

Big Data and Information Processing in Organizational Decision Processes

Data-centric approaches such as big data and related approaches from business intelligence and analytics (BI&A) have recently attracted major attention due to their promises of huge improvements in organizational performance based on new business insights and improved decision making. Incorporating data-centric approaches into organizational decision processes is challenging, even more so with big data, and it is not self-evident that the expected benefits will be realized. Previous studies have identified the lack of a research focus on the context of decision processes in data-centric approaches. By using a multiple case study approach, the paper investigates different types of BI&A-supported decision processes, and makes three major contributions. First, it shows how different facets of big data and information processing mechanism compositions are utilized in different types of BI&A-supported decision processes. Second, the paper contributes to information processing theory by providing new insights about organizational information processing mechanisms and their complementary relationship to data-centric mechanisms. Third, it demonstrates how information processing theory can be applied to assess the dynamics of mechanism composition across different types of decisions. Finally, the study’s implications for theory and practice are discussed.     

Business curriculum redesign: Integrating data analytics

Data analytics is an integral part of planning and decision making in business. Priorities have shifted to hiring skilled employees to support a company’s analytics requirements. The authors discuss the background of big data and data analytics, demand for trained professionals, and information on the development of a data analytics curriculum. Curriculum design models are explored and emphasis placed on university curriculum redesign. This is a perspective piece that also addresses interdisciplinary collaboration, accreditation, and related challenges.     

Comparing Business Intelligence and Big Data Skills

While many studies on big data analytics describe the data deluge and potential applications for such analytics, the required skill set for dealing with big data has not yet been studied empirically. The difference between big data (BD) and traditional business intelligence (BI) is also heavily discussed among practitioners and scholars. We conduct a latent semantic analysis (LSA) on job advertisements harvested from the online employment platform monster.com to extract information about the knowledge and skill requirements for BD and BI professionals. By analyzing and interpreting the statistical results of the LSA, we develop a competency taxonomy for big data and business intelligence. Our major findings are that (1) business knowledge is as important as technical skills for working successfully on BI and BD initiatives; (2) BI competency is characterized by skills related to commercial products of large software vendors, whereas BD jobs ask for strong software development and statistical skills; (3) the demand for BI competencies is still far bigger than the demand for BD competencies; and (4) BD initiatives are currently much more human-capital-intensive than BI projects are. Our findings can guide individual professionals, organizations, and academic institutions in assessing and advancing their BD and BI competencies.     

The questions we ask: Opportunities and challenges for using big data analytics to strategically manage human capital resources

Big data analytics have transformed research in many fields, including the business areas of marketing, accounting and finance, and supply chain management. Yet, the discussion surrounding big data analytics in human resource management has primarily focused on job candidate screenings. In this article, we consider how significant strategic human capital questions can be addressed with big data analytics, enabling HR to enhance overall firm performance. We also examine how new data sources that help assess workforce performance in real time can assist in the identification and development of the knowledge stars that contribute to firm performance disproportionately as well as help reinforce firm capabilities. But in order for big data analytics to be successful in the HR field, regulatory and ethical challenges must also be addressed; these include privacy concerns and, in Europe, the General Data Protection Regulation (GDPR). We conclude by discussing how big data analytics can facilitate strategic change within HR and the organization as a whole.     

Advanced technologies and international business: A multidisciplinary analysis of the literature

Advanced digital technologies, such as the Internet of Things, blockchain, big data analytics and augmented reality, are gradually transforming the way multinational firms do business. Due to the extent of this transformation many scholars argue that the integration of these technologies marks the commencement of the fourth industrial revolution (Industry 4.0). However, the question how these advanced technologies impact international business activities needs further attention. To this end, we adopt a multidisciplinary approach to review the related literature in international business (IB), general management, information systems, and operations research. We include the two latter fields, because advanced technologies have received more attention in these bodies of literature. Based on our analysis, we discuss the implications of these technologies for international business. Further, we highlight the drivers of technology utilisation by multinational firms and likely outcomes. We also provide future research avenues.     

Measuring Electronic Commerce Technology–Enabled Business Value: An Empirical Investigation

This research investigates whether firms using e-commerce technologies are successful in generating business value and, if so, which e-commerce drivers determine this success and how firms should use these drivers. There is no systematic empirical evidence in the IT productivity and business value literature regarding the payoffs a business receives from its e-business initiatives. The current research contributes to the literature in the e-commerce area by identifying a set of e-business value constructs, incorporating these constructs in a model in a manner not done before, and empirically validating the model using an Analysis of MOment Structures (AMOS)/?Structural Equation Modeling (SEM) analysis. The present research also contributes to the e-business value literature by providing insights into causal relationships among Rogers' innovation and diffusion theory (IDT) factors. This is the first time a research study has empirically established comprehensive causal relationships among these factors. The SEM analysis of the model indicates that the proposed model is able to explain e-commerce success utilizing the constructs identified and grounded using IT business value literature and Rogers' IDT. We conclude by summarizing its contributions to the IT literature, in general, and the e-business literature, in particular, and by providing insights for practice and suggestions for future research.     

Investigating a neglected part of Schumpeter’s creative army: what drives new-to-the-market innovation in micro-enterprises?

This paper tests a theoretical model to evaluate e-business capability and value in the fast growth small-to-medium enterprise (SME) context. We propose that e-business value depends on how fast growth SMEs deploy IT resources, strategic planning, culture, and business partnerships to develop e-business capability and business process competence which help these companies to achieve outstanding business performance. Structural equation modelling is employed to test our theoretical conceptualization on a cohort of 310 Australian fast growth SMEs across different industrial sectors. The results show that IT resources, strategic IT alignment, market orientation, and business partnerships do contribute significantly and indirectly to SME performance through the development of e-business capability and business process competence. Our study provides an initial empirical evidence to understand the relationship between IT and entrepreneurial SME performance. These findings have important implications for research and business practices.     

Cloud computing capability: its technological root and business impact

Cloud computing can help organizations create business value for long-term viability and sustainability by providing flexibility and versatility. We report a systematic analysis of the central role of cloud computing capability in bridging the information technology (IT) features of cloud computing and its business value. We posit that the IT features of cloud computing lead to measureable increase in business value on both dimensions of performance benefit and collaboration benefit through cloud computing capability. Survey data collected from 174 firms largely support our hypotheses. This study offers fine-grained insights into the mechanisms of how the IT features of cloud computing influence the business value stemming from cloud computing. Firms should focus more on cultivating organizational capabilities to effectively deploy cloud computing in order to harvest the benefits promised by cloud computing.     

Business analytics: Why now and what next?

Business analytics is a revolution that is impossible to miss. At its core, business analytics is about leveraging value from data. Instead of being referred to as the ‘sludge of the information age,’ data has recently been deemed ‘the new oil.’ While data can be employed for purposes such as detecting new opportunities, identifying market niches, and developing new products and services, it is also notoriously amorphous and hard to extract value from. In this Guest Editors’ Perspective, we first present a structural framework for deriving value from business analytics. Extracting value from data requires aligning strategy and desirable behaviors to business performance management in conjunction with analytic tasks and capabilities. We then introduce three special articles that provide in-depth insights regarding how business analytics is being employed in the management of healthcare, accounting, and supply chains.     

The Influence of Partner Knowledge Complementarities on the Effectiveness of IT Outsourcing

Despite the importance of knowledge complementarities to inter-firm cooperation, few researchers in information systems (IS) have examined, to date, the construct of knowledge complementarities (KC), and none have examined its role in the success of IT outsourcing alliances. In this paper, we distinguish between potential knowledge complementarities (PKC) and synergistic value, which comprise KC. PKC is conceptualized as a multidimensional construct encompassing knowledge types (similar and specialized) and knowledge domains (business and IT). Further, we examine the extent to which PKC between the client and the vendor promotes success in IT outsourcing alliances. This research also includes relative absorptive capacity because it is relevant when complementary knowledge flows between organizations. We used data from a field study of 81 firms in Korea to test the proposed model. Our findings indicate that each dimension of PKC contributes uniquely to knowledge complementarities. The results also show that PKC is significantly associated with IT outsourcing effectiveness. Relative absorptive capacity is found to be a moderator between PKC and IT outsourcing effectiveness. The theoretical and practical implications of these findings are discussed in the paper.     

Big data in an HR context: Exploring organizational change readiness,employee attitudes and behaviors

This research highlights a contextual application for big data within a HR case study setting. This is achieved through the development of a normative conceptual model that seeks to envelop employee behaviors and attitudes in the context of organizational change readiness. This empirical application considers a data sample from a large public sector organization and through applying Structural Equation Modelling (SEM) identifies salary, job promotion, organizational loyalty and organizational identity influences on employee job satisfaction (suggesting and mediating employee readiness for organizational change). However in considering this specific context, the authors highlight how, where and why such a normative approach to employee factors may be limited and thus, proposes through a framework which brings together big data principles, implementation approaches and management commitment requirements can be applied and harnessed more effectively in order to assess employee attitudes and behaviors as part of wider HR predictive analytics (HRPA) approaches. The researchers conclude with a discussion on these research elements and a set of practical, conceptual and management implications of the findings along with recommendations for future research in the area.     

The value of business managers' ‘Information Technology’ competence

This study analyses the role of general managers and their competence in information technologies (ITs) in the integration of these technologies in knowledge-intensive businesses. From a resource-based view, it assesses the effect of managers' IT knowledge and vision on information management in their organizations. It focuses on two knowledge industries: telecommunication and biotechnology, with a final sample of 122 firms. Structural equations are used to assess the data. The findings show that the role of managers goes further than supporting and championing ITs. They are direct key actors in the IT–business integration. For this reason, managers should understand IT potential and information system management in order to combine this knowledge with their unique strategic vision of the business, foreseeing opportunities and needs.     

Global integration strategies of small and medium multinationals: Evidence from Taiwan

This study replicates and extends Birkinshaw et al.’s (1995) model of the predictors of business unit integration of large Western multinational corporations (MNCs). Our study investigates the global integration strategies of Taiwanese small and medium sized enterprises (SMEs) competing in the global information technology (IT) industry. It confirms the importance of some structural forces (i.e. economies of scale and standard market demands) in the global integration strategies of Taiwanese SMEs thereby expanding the applicability of existent internationalization theories developed primarily in the context of large Western MNCs to non-Western SMEs. This study finds three results that add new knowledge to the current SME literature and provides managerial implications. First, it finds a negative relationship between competitive actions and business unit integration. Second, it finds that in the optimally globalized IT industry there is no direct effect of business unit integration on performance. Third, it finds a direct effect of differential comparative advantage on performance.     

Implementing Big Data Analytics in Small Firms: A Situated Human Practice Approach

This study identifies and addresses an important gap in the nascent literature on big data analytics, using a longitudinal case study to investigate the implementation and application of big data analytics into a small firm specialized in transport logistics. Our research is rooted in Practice Theory, considering the implementation of new technologies in organizations as a result of multiple social negotiations, interpretations, and interactions. Our findings indicate the importance and centrality of human factors in decision-making and operational implementation, technology representing only a means to a clearly specified and collectively assumed objective. Big data analytics adoption and use in the case-study firm represents a gradual process, with each stage justified by the need to solve the problems caused by heavy and unpredictable road traffic. This approach validates the entrepreneurial effectuation model, which defines a firm's strategy as a fragmented but continuous effort to find and implement effective solutions to the market challenges encountered.