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The authors study how cloud adoption decision making unfolds in organizations and present the dynamic process leading to a decision to adopt or reject cloud computing. The authors thus complement earlier literature on factors that influence cloud adoption.

The authors adopt an interpretive epistemology to understand the process of cloud adoption decision making. Following an empirical investigation drawing on interviews with senior managers who led the cloud adoption decision making in organizations from across Europe. The authors outline a framework that shows how cloud adoptions follow multiple cycles in three broad phases.

The study findings demonstrate that cloud adoption decision making is a recursive process of learning about cloud through three broad phases: building perception about cloud possibilities, contextualizing cloud possibilities in terms of current computing resources and exposing the cloud proposition to others involved in making the decision. Building on these findings, the authors construct a framework of this process which can inform practitioners in making decisions on cloud adoption.

This work contributes to authors understanding of how cloud adoption decisions unfold and provides a framework for cloud adoption decisions that has theoretical and practical value. The study further demonstrates the role of the decision-leader, typically the CIO, in this process and identifies how other internal and external stakeholders are involved. It sheds light on the relevance of the phases of the cloud adoption decision-making process to different cloud adoption factors identified in the extant literature.

This systematic literature review aims to explore the adoption, global acceptance and implementation of human resources (HR) analytics (HRA) by reviewing literature on the subject. HRA adoption can assist HR professionals in managing complex procedures and making strategic human resource management (SHRM) decisions more effectively. The study also aims to identify the applications of analytics in various disciplines of management.

The review is conducted using a domain-based structured literature review (SLR), emphasizing the diffusion of innovative thinking and the adoption process of HRA among early adopters. The philosophical stances are analyzed with the combination of research onion model and PRISMA protocol. Secondary data are gathered from published journals, books, case studies, conference proceedings, web pages and media stories as the primary source of information.

The study finds that skilled professionals and management assistance can significantly impact adoption intentions, enabling professionals to deal with analytics. The examples and analytical models provided by early adopters allow managers to manage complex processes and make SHRM decisions.

The study suggests that the lack of use of quantitative techniques is a key limitation and should be considered in future studies. Despite the rise in the number of research papers on HRA, its application in the workplace remains limited.

This research can assist managers in implementing HRA and help resolve complex and inefficient processes, making SHRM decisions.

This study adds to the existing body of knowledge on how HRA can aid a company's efficacy and performance and can be considered one of the first to link adoption and HRA.

Given the complexity of building information modeling (BIM) adoption decisions in small- and medium-sized enterprises (SMEs) in the Architecture, Engineering and Construction (AEC) industry, understanding BIM adoption decision-making through the net effect of a single factor on BIM adoption decisions alone is limited. Therefore, this paper analyzed the co-movement effect of managers' psychological factors on the BIM adoption decisions from the perspective of managers' perceptions. The purpose is to let managers have a deep understanding of their BIM adoption decisions, and put forward targeted suggestions for the AEC industry to promote the adoption of BIM by SMEs.

Data from 192 managers in SMEs collected by the questionnaire were used in a fuzzy set qualitative comparative analysis (fsQCA). Due to the limitations of fsQCA in making the best use of the data used, as a complement to fsQCA, necessary conditions analysis (NCA) was used to analyze the extent to which necessary conditions influenced the outcome.

(1) NCA analysis shows that high perceived resource availability (PRA) and high performance expectancy (PE) are necessary conditions for high BIM adoption intention (AI). (2) fsQCA analysis shows that high PE is the single core condition for high AI. fsQCA analysis identifies three configurations of managers' psychological factors, reflecting three types of managers' decision preferences, namely benefit preference, loss aversion and risk avoidance, respectively. Different decision preferences may lead to different BIM adoption strategies, such as full in-house use, partial in-house/outsourcing and full outsourcing of BIM processes. (3) High perceived risk (PR) and low perceived business value of BIM (PBV) are the core conditions for low AI.

This paper expands on the application of fsQCA to context of BIM adoption decisions. Based on the results of fsQCA analysis, this paper also establishes the relationship between managers' decision-making psychology and BIM adoption strategy choice and analyzes the impact of different decision biases on BIM adoption strategy choice. It concludes with suggestions for encouraging managers to adopt BIM and for avoiding decision-making bias.

The purpose of this paper is to propose that adoption of new ideas is a more involved cognitive process than has been recognised and this paper seeks to redress the trivialisation of ideas as emerging management ideas (“fads”). The embracing of “fads” for performance improvement and competitive advantage has received considerable attention in the academic literature, resulting in a rather one-sided view.

Cognitive decision-making, evidence-based management and complexity theory are examined to illustrate cognitive process, skills and experiences used when making decisions and several propositions are derived from these ideas.

An conceptual model of “fad” adoption, integrating the ideas and propositions is presented. This model provides a more pragmatic examination of “fad” adoption decisions and encourages an in depth consideration of their introduction. The model offers a more sophisticated, focused tool for examining the adoption of new management ideas and provides a springboard from which more detailed, integrated models can be developed, and hopefully will stimulate discussion. Implications for theory and practice are also considered.

Examination of the literature on management “fads” revealed significant material that focused on the negative aspects of “fad” adoption, but an absence of material that examined how manager’s made their adoption decisions. This paper, therefore, provides a valuable contribution to both theory and practice by examining factors which contribute to how and why management decisions to adopt “fads” are made and develops a model to illustrate how these are integrated to contribute to the process of decision-making.

While a substantial number of studies have examined information behaviour, most centred on choice of information source, student information behaviour, information behaviour of women, environmental uncertainty and scanning behaviour of top-level hotel executives. However, little is known about how the small and medium enterprise (SME) managers scan, seek, gather, document and use information relevant for emerging information and communication technology (EICT) adoption decision-making. This paper aims to examine the key success factors influencing SME manager’s information behaviour on EICT adoption decision-making.

This study deploys a qualitative approach to exploring 16 key success factors shaping SME managers’ information behaviour on EICT adoption decision-making. More specifically, the study adopted both unstructured and semi-structured interviews with 20 small business managers drawn purposeful from Crunch Database.

This study develops an extended technology, organisation and environment framework by incorporating the information context which helped to unravel 16 key success factors influencing small business managers’ information behaviour on EICT. From the technology context, uncertainty driven, compatibility, replacement of legacy technology, relative advantages, lack of technical know-how and perceived affordability fit for purpose influence SME managers’ information behaviour. Users’ acceptance information, efficiency driven, owner’s support shape the organisation context of perceived information need; competitor’s intelligence gathering, customer’s information gathering provider credibility and government policy influence the environmental context of perceived information need; and finally, perceived information sources credibility, herding event, testimonial and openness to other people’s ideas and experiences are shaped by the information context.

Qualitative research is normally subjective, interpretive and limited on the sample used. Because of the limited number of interviews, the generalisation of the framework and the finding is difficult. Therefore, the finding and the framework need to be established across broader population. The findings are vital considering the fact that small business managers are limited in knowledge and the study may improve the way and manner they go about seeking and gathering information relevant in adopting new ICT.

This research provides further insight into SME managers’ information behaviour by developing a framework and identifying main factors influencing SMEs information behaviours on EICT. Therefore, understanding such factors will enrich their knowledge on some of the factors that may shape their decisions during EICT adoption decision to make effective decision.

This study aims to analyze the influence of farmers’ degree of participation in collective action on their adoption decisions and waiting time regarding soil and water conservation (SWC) measures.

The Probit model and Generalized Propensity Score Match method are used to assess the effect of the degree of participation in collective action on farmers’ adoption decisions and waiting time for implementing SWC measures.

The findings reveal that farmers’ engagement in collective action positively influences the decision-making process regarding terrace construction, water-saving irrigation and afforestation measures. However, it does not significantly impact the decision-making process for plastic film and ridge-furrow tillage practices. Notably, collective action has the strongest influence on farmers’ adoption decisions regarding water-saving irrigation technology, with a relatively smaller influence on the adoption of afforestation and terrace measures. Moreover, the results suggest that participating in collective action effectively reduces the waiting time for terrace construction and expedites the adoption of afforestation and water-saving irrigation technology. Specifically, collective action has a significantly negative effect on the waiting time for terrace construction, followed by water-saving irrigation technology and afforestation measures.

The results of this study underscore the significance of fostering mutual assistance and cooperation mechanisms among farmers, as they can pave the way for raising funds and labor, cultivating elite farmers, attracting skilled labor to rural areas, enhancing the adoption rate and expediting the implementation of terraces, water-saving irrigation technology and afforestation measures.

Drawing on an evaluation of farmers’ degree of participation in collective action, this paper investigates the effect of participation on their SWC adoption decisions and waiting times, thereby offering theoretical and practical insights into soil erosion control in the Loess Plateau.

Smart card-based E-payment systems are receiving increasing attention as the number of implementations is witnessed on the rise globally. Understanding of user adoption behavior of E-payment systems that employ smart card technology becomes a research area that is of particular value and interest to both IS researchers and professionals. However, research interest focuses mostly on why a smart card-based E-payment system results in a failure or how the system could have grown into a success. This signals the fact that researchers have not had much opportunity to critically review a smart card-based E-payment system that has gained wide support and overcome the hurdle of critical mass adoption. The Octopus in Hong Kong has provided a rare opportunity for investigating smart card-based E-payment system because of its unprecedented success. This research seeks to thoroughly analyze the Octopus from technology adoption behavior perspectives.

Cultural impacts on adoption behavior are one of the key areas that this research posits to investigate. Since the present research is conducted in Hong Kong where a majority of population is Chinese ethnicity and yet is westernized in a number of aspects, assuming that users in Hong Kong are characterized by eastern or western culture is less useful. Explicit cultural characteristics at individual level are tapped into here instead of applying generalization of cultural beliefs to users to more accurately reflect cultural bias. In this vein, the technology acceptance model (TAM) is adapted, extended, and tested for its applicability cross-culturally in Hong Kong on the Octopus. Four cultural dimensions developed by Hofstede are included in this study, namely uncertainty avoidance, masculinity, individualism, and Confucian Dynamism (long-term orientation), to explore their influence on usage behavior through the mediation of perceived usefulness.

TAM is also integrated with the innovation diffusion theory (IDT) to borrow two constructs in relation to innovative characteristics, namely relative advantage and compatibility, in order to enhance the explanatory power of the proposed research model. Besides, the normative accountability of the research model is strengthened by embracing two social influences, namely subjective norm and image. As the last antecedent to perceived usefulness, prior experience serves to bring in the time variation factor to allow level of prior experience to exert both direct and moderating effects on perceived usefulness.

The resulting research model is analyzed by partial least squares (PLS)-based Structural Equation Modeling (SEM) approach. The research findings reveal that all cultural dimensions demonstrate direct effect on perceived usefulness though the influence of uncertainty avoidance is found marginally significant. Other constructs on innovative characteristics and social influences are validated to be significant as hypothesized. Prior experience does indeed significantly moderate the two influences that perceived usefulness receives from relative advantage and compatibility, respectively. The research model has demonstrated convincing explanatory power and so may be employed for further studies in other contexts. In particular, cultural effects play a key role in contributing to the uniqueness of the model, enabling it to be an effective tool to help critically understand increasingly internationalized IS system development and implementation efforts. This research also suggests several practical implications in view of the findings that could better inform managerial decisions for designing, implementing, or promoting smart card-based E-payment system.

Visual analytics is increasingly becoming a prominent technology for organizations seeking to gain knowledge and actionable insights from heterogeneous and big data to support decision-making. Whilst a broad range of visual analytics platforms exists, limited research has been conducted to explore the specific factors that influence their adoption in organizations. The purpose of this paper is to develop a framework for visual analytics adoption that synthesizes the factors related to the specific nature and characteristics of visual analytics technology.

This study applies a directed content analysis approach to online evaluation reviews of visual analytics platforms to identify the salient determinants of visual analytics adoption in organizations from the standpoint of practitioners. The online reviews were gathered from Gartner.com, and included a sample of 1,320 reviews for six widely adopted visual analytics platforms.

Based on the content analysis of online reviews, 34 factors emerged as key predictors of visual analytics adoption in organizations. These factors were synthesized into a conceptual framework of visual analytics adoption based on the diffusion of innovations theory and technology–organization–environment framework. The findings of this study demonstrated that the decision to adopt visual analytics technologies is not merely based on the technological factors. Various organizational and environmental factors have also significant influences on visual analytics adoption in organizations.

This study extends the previous work on technology adoption by developing an adoption framework that is aligned with the specific nature and characteristics of visual analytics technology and the factors involved to increase the utilization and business value of visual analytics in organizations.

This study highlights several factors that organizations should consider to facilitate the broad adoption of visual analytics technologies among IT and business professionals.

This study is among the first to use the online evaluation reviews to systematically explore the main factors involved in the acceptance and adoption of visual analytics technologies in organizations. Thus, it has potential to provide theoretical foundations for further research in this important and emerging field. The development of an integrative model synthesizing the salient determinants of visual analytics adoption in enterprises should ultimately allow both information systems researchers and practitioners to better understand how and why users form perceptions to accept and engage in the adoption of visual analytics tools and applications.

Three-dimensional (3D) printing (3DP) offers a promising value proposition across multiple manufacturing industries. Despite the variety of production benefits the technology entails, its rate of adoption is still low compared to industry forecasts. In face of this challenge, industry as well as academia requires more information and guidance. This review aims to examine the characteristics of the existing body of research on the organizational adoption of 3DP as well as its underlying theoretical concepts. The most common criteria driving adoption will be derived, such as to facilitate the managerial decision-making process. Pathways for future research will be presented.

This study underlies a bibliometric literature review and additionally applies content analysis to systematically investigate the existing body of research and group decision criteria along the four major pillars of strategic decision-making.

The contributions of this paper are threefold. First, the bibliometric analysis reveals interesting aspects of the existing body of research. The most prominent characteristics of the contemporary literature are reflected along descriptive indicators, such as industry, method, model, origin, research outlet or adoption drivers, thus granting relevant insights into academia and practice. Second, the most notable adoption models are carefully analyzed on their inherent attributes and their application fit for the context of organizational 3DP adoption. Findings, for instance, revealed the dominance of diffusion of innovation (DOI) across the existing body of research and divulge that this construct is generally applied in combination with user-centered decision frameworks to yield more precise results. Third, an ample range of opportunities for future research are detected and thoroughly explained. Among others, the authors identified a clear lack of information on the impact environmental variables and contingency factors exerted on the organizational adoption of 3DP. Guidance in relation to the sourcing of industry data, usage of adoption frameworks and avenues for future scientific projects is supplied.

This study represents the first semi-systematic literature review on the organizational adoption of 3DP. Thus, it not only offers a valuable evaluation guide for potential adopters but also determines a future research agenda.

The use of computer-assisted audit techniques and tools (CAATTs) is a part of many professionally recommended audit procedures. This paper aims to argue that obtaining a better understanding of the factors underlying successful CAATTs adoptions would be helpful to aid wider development of these technologies in internal audit functions.

To help develop the understanding of the factors that lead to successful adoption of GAS, this paper uses current theories that are seeking to better explain the various elements that constitute IT adoption processes. In particular, it makes use the “Unified Theory of Acceptance and Use of Technology” (UTAUT). UTAUT is used to structure the analysis of ten semi-structured, qualitative, interviews of key decision-makers in adoptions of CAATTS in internal audit functions in exploring the key factors that drove the successful adoption of these IT technologies. The most widely used CAATTs tools available to internal auditors is currently GAS. This study specifically focuses on GAS tools.

This paper explores the successful adoption of GAS in ten cases to draw out the general factors that appear to be essential elements that lead to successful adoptions. From this basis, the paper proposes an initial model, built on existing theories of IT adoption more generally, as a theoretical basis for GAS adoption by decision-makers in an internal audit setting to better understand what may be essential factors to their adoption decisions to be likewise successful. Results suggest that two constructs from UTAUT (performance expectancy and facilitating conditions) appear to be particularly important factors influencing successful adoptions of GAS in this domain. However, the UTAUT constructs of social influence and effort expectancy are not found by this study to be as important in this specific IT adoption domain. UTAUT also proposes four moderating factors that influence the constructs. This paper explores two of these moderators – experience and voluntariness – and shows that both are keys to the constructs application to this domain.

The paper examines the motivation for CAATTs adoption by internal auditors using the UTAUT framework commonly used in information system research but not so to date in this domain where there is professional guidance suggesting wider use of technology should be made compared to actual usage.