Market perception on cloud computing initiatives in organizations: An extended resource-based view

Effect of blockchain technology initiatives on firms' market value

Despite blockchain's potential to transform corporations by providing new ways of organizing business processes and handling information, extant research pays inadequate attention to how and under what conditions blockchain technology provides additional financial value for shareholders. Drawing on the efficient market hypothesis and signaling theory, we examined the relationship between firms' blockchain use, development announcements, and stock market reactions. We used the event study methodology to analyze a sample of blockchain projects initiated by US firms between 2016 and 2019. The sample contains 114 firm-event observations. The findings show that the average abnormal return over a 2 days event period (including the day of the announcement and the day after the announcement) was positive. This positive stock market reaction is even more substantial when firms announce blockchain projects that focus on saving cost or time. Our findings also indicate that blockchain announcements tend to elicit more positive market reactions from smaller firms. We analyzed 249 firm-event observations containing firms from around the world and conclude that blockchain technology has a non-significant long-term impact on operating performance. The contingency approach adopted in our research provides advice for selecting the right mix of blockchain investment initiatives that is most suitable for a given organizational context.

The impact of business analytics capabilities on innovation, information quality, agility and firm performance: the moderating role of industry dynamism

Purpose

As businesses keep investing substantial resources in developing business analytics (BA) capabilities, it is unclear how the performance improvement transpires as BA affects performance in many different ways. This paper aims to analyze how BA capabilities affect firms’ agility through resources like information quality and innovative capacity considering industry dynamism and the resulting impact on firm performance.

Design/methodology/approach

This paper tested the research hypothesis using primary data collected from 192 companies operating in Bangladesh. The data were analyzed using partial least squares-based structural equation modeling.

Findings

The results indicate that BA capabilities improve business resources like information quality and innovative capacity, which, in turn, significantly impact a firm’s agility. This paper also found out that industry dynamism moderates the firms’ agility and, ultimately, firms’ performance.

Practical implications

The contribution of this work provides insight regarding the role of business analytics capabilities in increasing organizational agility and performance under the moderating effects of industry dynamism.

Originality/value

The present research is to the best of the authors’ knowledge among the first studies considering a firm’s agility to explore the impact of BA on a firm’s performance in a dynamic environment. While previous researchers discussed resources like information quality and innovative capability, current research theoretically argues that these items are a leveraging point in a BA context to increase firm agility.

Shareholder wealth implications of software firms' transition to cloud computing: a marketing perspective

Moving into cloud computing represents a major marketing shift because it replaces on-premises offerings requiring large, up-front payments with hosted computing resources made available on-demand on a pay-per-use pricing scheme. However, little is known about the effect of this shift on cloud vendors' financial performance. This study draws on a longitudinal data set of 435 publicly listed business-to-business (B2B) firms within the computer software and services industries to investigate, from the vendors' perspective, the shareholder wealth effect of transitioning to the cloud. Using a value relevance model, we find that an unanticipated increase in the cloud ratio (i.e., the share of a firm's revenues from cloud computing) has a positive and significant effect on excess stock returns; and it has a negative and significant effect on idiosyncratic risk. Yet these effects vary across market structures and firms. In particular, unanticipated increases in market maturity intensify the positive effect of moving into the cloud on excess stock returns. Further, unexpected increases in advertising intensity strengthen the negative effect of shifting to the cloud on idiosyncratic risk.

Efficiency or Innovation?

Considering the mixed arguments and uncertainty about the payoff of cloud computing, this paper empirically studies the long-term cloud computing impact on the financial performance, specifically from the perspective of efficiency and innovation. Taking 253 pairs of listed companies in China as the research sample, propensity score matching and difference in differences techniques combined with OLS regression are conducted to analyze a rolling 5-year panel data. The analysis results show that cloud computing adoption leads to years of financial performance decline followed by an upturn. The downward trend is more pronounced when it is adopted with innovation. This paper contributes to the existing literatures by leveraging archival performance data to verify the long-term business value and revealing the value realization difference between efficiency- and innovation-oriented cloud computing adoptions. The findings remind the managers to see the two sides of cloud computing and make rational adoption decisions, especially cloud-based innovation, according to their actual situations.

Does marketing analytics capability boost firms' competitive marketing performance in data-rich business environment?

Purpose

Few well-documented studies have explained the importance of researching firms' marketing analytics capability (FMAC). In spite of its significance, there is scant attention to conceptualising and empirically investigating FMAC and its consequences in a data-driven business context. Thus, this study aims to develop and test a conceptual model that relates FMAC and its repercussions in the data-rich business environment.

Design/methodology/approach

This study analysed the data from 250 managers amongst large and medium-sized manufacturing and service-intensive firms. Furthermore, this research performed an empirical study by using operationalised questionnaire survey method to verify the hypotheses and reach its theoretical and managerial implications. Structural equation modelling with maximum-likelihood estimation method was applied to verify the validity of the proposed research model.

Findings

Multivariate analysis results show that FMAC significantly influences firms' competitive marketing performance (FCMP) with the presence of holistic marketing decision-making (HMDM) as a mediator. Moreover, adoption of artificial intelligence (AAI) enhances the relationship of FMAC-HMDM and FMAC-FCMP linkages.

Practical implications

This study analyses how FMAC can enhance FCMP and contributes to resource-based views and technological capability theories. From a managerial perspective, guidelines are provided for marketers to adopt advance technologies, such as AI, to optimise FMAC and HMDM to achieve competitive marketing performance.

Originality/value

Believing that “how to be competitive in marketing performance under data-rich-environment”, this research is the first to use the data of a firm manager to facilitate the understanding of FMAC, which provides a new direction for improving marketing performance. In addition, HMDM and AAI are also proposed for firms to optimise FCMP.

Analyzing Continuance of Cloud Computing in Higher Education Institutions: Should We Stay, or Should We Go?

Higher Education Institutions (HEIs) consider resource optimization as an essential concern. Cloud computing (CC) in the fourth industrial revolution became the de-facto standard for delivering IT resources and services. CC is now a mainstream technology, andHEIs across the globe are rapidly transitioning to this model; hence, maintaining the retention of the customers of such technologies is challenging for cloud service providers. Current research concerning CC focused on adoption and acceptance. However, there is still a scarcity of research concerning such technology’s continued use in an organizational setting. Drawing on the prior literature in organizational-level continuance, this paper established a positivist quantitative-empirical study to bridge the research gap and assess the precursors for a continuance of cloud technology in HEIs. Subsequently, this study developed a conceptual framework by integrating the IS success model and the IS discontinuance model through the lens of the TOE framework. The data were collected from the decision-makers of Malaysian HEIs that have adopted CC services, and analyzed using Structural equation Modelling (SEM) based on Partial Least Squares (PLS). The results indicate that the continuance intention can be predicted by technology, organizational, environmental, and other contextualized factors, explaining 85.2% of the dependent variables’ variance. The paper closes with a discussion of the research limitations, contribution, and future directions.

Current and Future Contributing Factors and Trends in the Usage of IT Cloud Computing in Manufacturing and Service Sectors

Cloud computing provides organisations with the ability to quickly change infrastructure, provider and service levels. The study looks at factors affecting the usage of cloud computing by organisations in the manufacturing and service sectors in the United States. Extrinsic motivation was found to be a significant factor for change in cloud computing budget allocation in manufacturing, whereas intrinsic motivation was a significant factor in the service sector. The study also shows that organisations’ future budgets include internal and external sources to fulfil their IT needs.

Continuance Use of Cloud Computing in Higher Education Institutions: A Conceptual Model

Resource optimization is a key concern for Higher Education Institutions (HEIs). Cloud Computing, as the recent generation in computing technology of the fourth industrial revolution, has emerged as the main standard of service and resource delivery. As cloud computing has grown into a mature technology and is being rapidly adopted in many HEIs across the world, retaining customers of this innovative technology has become a challenge to the cloud service providers. Current research trends on cloud computing have sought to study the acceptance or adoption of technology; however, little research has been devoted to the continuance use in an organizational setting. To address this gap, this study aims to investigate the antecedents of cloud computing continuance use in HEIs. Hence, drawing on the prior literature in organizational-level continuance, this research established a conceptual model that extends and contextualizes the IS continuance model through the lens of the TOE framework (i.e., technological, organizational, and environmental influences). The results of a pilot study, conducted through a survey with information and communications technology (ICT) decision makers, and based on the proposed conceptual model, indicate that the instrument is both reliable and valid, and so point the way towards further research. The paper closes with a discussion of the research limitations, contribution, and future directions.

Cloud computing technology adoption: an evaluation of key factors in local governments

Purpose

The significance of cloud services in information technology (IT) is increasing as a means of achieving enhanced productivity, efficiency and cost reduction. Through cloud-based service, the reliability and scalability of an organization’s systems can be enhanced since organizations such as local governments are able to concentrate on their main business strategies. This research seeks to identify critical factors that may have an impact on the acceptance of cloud-based services, where the organizational context is based on local governments in Australia.

Design/methodology/approach

To formulate a more comprehensive IT innovation adoption model for cloud technology, factors from the technology-organizational-environment framework, desires framework and diffusion of innovation model were integrated. Data was obtained from 480 IT staff working in 47 local government organizations.

Findings

The research results show that the factors which had a statistically significant and positive impact on the adoption of cloud-based services in local governments were compatibility, complexity, cost, security concerns, expected benefits and organization size. It is likely that the outcomes from this research will provide insights to any organization seeking to make investment decisions on the adoption of cloud-based services.

Research limitations/implications

Limitations include generalizability of the findings since the data is restricted to local government areas in Queensland, Australia. Further, the sample mostly included individuals with managerial positions and may not completely capture the cloud adoption factors relevant for front line IT employees. Another limitation is the possible omission of factors that may be relevant but not considered due to the selected theories. Lastly, this research did not differentiate between different types of cloud adoption such as private, public, community and hybrid models that are possible in this context.

Originality/value

The paper provides a combination framework of cloud-based service adoption based on a literature review on cloud adoption from an IS perspective. It adapts integrated model to establish a more comprehensive innovation adoption framework for cloud technology.

An Exploratory Study Of Factors Driving Decision Maker Intentions To Adopt Cloud Computing

United States based companies have invested more heavily in cloud services than companies in other nations. Despite numerous benefits claimed by cloud service providers, many organisations are still uncertain about the implementation of cloud computing. The aim of this study is to gain a better understanding of the factors that are important to the usage adoption decision of this information technology delivery model and the implications for organisations in the United States. Decision makers were surveyed to discover which attributes were important in their determination of cloud computing utilisation. Using a sample of executives from manufacturing and service sectors in the United States, multiple factors contributing to the recent growth in cloud computing have been identified using a factor analysis. Four factors emerged from the data analysis include extrinsic motivation, intrinsic motivation, perceived risks, and resource constraint.

Performance, farmer perception, and the routinisation (RO) moderation on ERP post-implementation

This study discusses the perceptions of the routinisation effects on the post-implementation and post-adoption of the enterprise resource planning (ERP) in farms. A theoretical model and nine hypotheses were proposed using factors according to the literature of resource-based view (RBV) approach and on the ERP impact on farm performance perceptions. This study contributes to the literature by testing empirically the moderation effect of routinisation on the RBV. A qualitative interview was applied to larger farmers where ERP was already in use and for the quantitative approach a sample of 448 answers was collected composed of 74% grain farmers, 14% cattle raising and milk producers, and 13% sugar cane and fruits farmers. The results reveal that the model explains 63% of the variation in the impact on farm performance. Our results show that routinisation moderates only the relationship between the impact on internal operations with impact on farm performance. The conclusions confirm the necessity to expand the RBV approach to the farmer perceptions, exploring other factors like the benefits and the impact of natural resources in the routinisation process. Finally, we propose a discussion of the development of Agriculture 4.0 in a resource-based view for the development of competitive advantage in the context of farms.

Analysis of Information Security News Content and Abnormal Returns of Enterprises

As information technologies and the Internet have rapidly evolved, businesses have begun to use them to improve communication efficiency within and outside the organization. However, applications of information technologies are accompanied by information delivery, personal data protection, and information security problems. There are potential risks inherent in any application of information technologies. Moreover, with the improvement of networking and computing capabilities, the impact of attacks from hackers and malicious software has also increased. A breach or leakage of important corporate data may not only damage the firm’s image but also sabotage the firm’s operation, resulting in financial losses. In this study, the content of information security news reports was analyzed in an attempt to clarify the association between information security news and corporate stock prices. Methods including decision trees, support vector machines (SVMs), and random forests were used to explore the associations of news related variables with abnormal returns. Results indicate that the news source and the presence of negative words in the news have an impact on abnormal returns.

Big data investments in knowledge and non-knowledge intensive firms: what the market tells us

Purpose

This paper aims to investigate the value of big data investments by examining the market reaction to company announcements of big data investments and tests the effect for firms that are either knowledge intensive or not.

Design/methodology/approach

This study is based on an event study using data from two stock markets in China.

Findings

The stock market sees an overall index increase in stock prices when announcements of big data investments are revealed by grouping all the listed firms included in the sample. Increased stock prices are also the case for non-knowledge intensive firms. However, the stock market does not seem to react to big data investment announcements by testing the knowledge intensive firms along.

Research limitations/implications

This study contributes to the literature on assessing the economic value of big data investments from the perspective of big data information value chain by taking an unexpected change in stock price as the measure of the financial performance of the investment and by comparing market reactions between knowledge intensive firms and non-knowledge intensive firms. Findings of this study can be used to refine practitioners’ understanding of the economic value of big data investments to different firms and provide guidance to their future investments in knowledge management to maximize the benefits along the big data information value chain. However, findings of study should be interpreted carefully when applying them to companies that are not publicly traded on the stock market or listed on other financial markets.

Originality/value

Based on the concept of big data information value chain, this study advances research on the economic value of big data investments. Taking the perspective of stock market investors, this study investigates how the stock market reacts to big data investments by comparing the reactions to knowledge-intensive firms and non-knowledge-intensive firms. The results may be particularly interesting to those publicly traded companies that have not previously invested in knowledge management systems. The findings imply that stock investors tend to believe that big data investment could possibly increase the future returns for non-knowledge-intensive firms.