Predicting e-readiness at firm-level: An analysis of technological, organizational and environmental (TOE) effects on e-maintenance readiness in manufacturing firms

Competitive organizational climate and artificial intelligence (AI) acceptance: the moderating role of leaders' power construal

Introduction

The incorporation of Artificial Intelligence (AI) in organizations is pivotal to deal with work-related tasks and challenges effectively, yet little is known about the organizational factors that influence AI acceptance (i.e., employee favorable AI attitudes and AI use). To address this limitation in the literature and provide insight into the organizational antecedents influencing AI acceptance, this research investigated the relationship between competitive organizational climate and AI acceptance among employees. Moreover, given the critical role of a leader in employee attitude and behavior, we examined the moderating role of leaders' power construal as responsibility or as opportunity in this relationship.

Methods

Study 1 was a three-wave field study among employees (N = 237, Mage = 38.28) working in various organizations in the UK. The study measured employees' perception of a competitive organizational climate at Time 1, leaders' power construal (as perceived by employees) at Time 2, and employee attitudes towards AI and their actual use of AI in the workplace at Times 2 and 3. Study 2 was a 2 (climate: highly competitive vs. low competitive) by 2 (power construal: responsibility vs. opportunity) experiment among employee participants (N = 150, Mage = 37.50).

Results

Study 1 demonstrated a positive relationship between competitive climate and employee AI use over time. Furthermore, both studies revealed an interaction between competitive climate and leader's power construal in the prediction of employee AI acceptance: In Study 1, competitive climate was negatively related to AI acceptance over time when leaders construed power as opportunity. In Study 2 competitive climate was positively related to AI acceptance when leaders construed power as responsibility rather than as opportunity.

Discussion

These results underscore the organizational factors that are required in order for employees to shape favorable attitudes towards AI and actually use AI at work. Importantly, this research expands the limited body of literature on AI integration in organizations.

Investigating the nexus between information technology capabilities, knowledge management, and green product innovation: evidence from SME industry

The aim of this study to investigate the relationship between information technology capabilities (ITCs) and green product innovation (GPI). The information technology (IT) capabilities with multiple dimensions, such as IT competence, IT integration, and IT infrastructure, were used in this paper. Moreover, to verify the deep relationship between ITCs and GPI, we used knowledge management (KM) as a mediator. The data were collected through a questionnaire from the senior managers, middle-level managers, and operational staff associated with the small- and medium-sized production industry of Pakistan. We collect data in two waves between January 2022 and July 2022. The data were analyzed through the partial least square structural equation modeling through SmartPLS 3.2.2. The findings of this study conclude. First, in the direct relationship, two IT capabilities, such as IT competence and IT infrastructure, have a positive and significant direct relationship with green product innovation, but IT integration has an insignificant relationship with green product innovation. Second, the results show that three IT capabilities have positively influenced knowledge management. Third, the results confirm that KM has a significant positive effect on GPI. Finally, the outcomes confirmed that knowledge management positively and significantly mediates between all IT capabilities and GPI in the indirect relationship.

Business environment as a determinant in the uptake of cyber-physical systems for facilities management – a Delphi study

Purpose

Incorporating digital technologies such cyber-physical systems (CPS) for facilities management (FM) functions is fast gaining attention. However, the rudiments for the effective espousal of such an innovative technology for the delivery of FM tasks have not received scholarly attention. In FM, the business environment is a vital component in achieving organisations’ stipulated objectives. Hence, this study aims to assess the influence of business environment factors in the adoption of CPS for FM activities.

Design/methodology/approach

A qualitative approach was adopted for the study using the Delphi technique. Experts were selected through a well-defined process that involved certain criteria. The opinions of the selected experts were gotten in two iterations that were subjected to analysis using statistics of measure for central tendency, and interquartile deviation to ascertain consensus among the experts, while Mann–Whitney U test was deployed in checking the difference in the views of the experts.

Findings

The results from the study indicated that eight business environment factors were of very high significance in determining the espousal of CPS for FM, while the other eight factors proved to be high significance. Also, there was no significant difference in the opinions of experts from academic institutions and professional practice.

Practical implications

The findings from the study would provide insight to organisations saddled with FM activities on the prevailing business environment factors that would be influential in adopting a digital technology such as CPS.

Originality/value

The study contributes immensely to the body of knowledge in the quest for digital transformation in FM delivery. It unveils the significant business environment factors that are influential in the drive for incorporating new innovations such as CPS for FM functions.

Managing healthcare supply chain through artificial intelligence (AI): A study of critical success factors

Healthcare is one of the most critical sectors due to its importance in handling public health. With the outbreak of various diseases, more recently during Covid-19, this sector has gained further attention. The pandemic has exposed vulnerabilities in the healthcare supply chain (HSC). Recent advancements like the adoption of various advanced technologies viz. AI and Industry 4.0 in the healthcare supply chain are turning out to be game-changers. This study focuses on identifying critical success factors (CSFs) for AI adoption in HSC in the emerging economy context. Rough SWARA is used for ranking CSFs of AI adoption in HSC. Results indicate that technological (TEC) factors are the most influential factor that impacts the adoption of AI in HSC in the context of emerging economies, followed by institutional or environmental (INT), human (HUM), and organizational (ORG) dimensions.

Adoption of artificial intelligence in financial services: a policy framework

Purpose

A crucial contemporary policy question for financial service organizations of being resilient across the globe calls for rethinking and renovating by adopting and adapting to the technologies of artificial intelligence (AI). The purpose of this study is to propose a policy framework for adoption of AI in the finance sector by exploring the driving factors through systems approach.

Design/methodology/approach

Based on literature review and discussions with experts from both industry and academia, nine enablers were shortlisted, which were used in the questionnaire survey to determine ranks of enablers. Further, the study developed the interpretive structural model (ISM) with the help of experts.

Findings

The ISM digraph developed with the help of the experts, resulted in the enablers like anticipated profitability, contactless solutions, credit risk management and software vendor support as dependent factors and stood at the top of the ISM. On the other hand, factors like availability of the data, technical infrastructure and funds are the most driving factors, which lie on the bottom of the ISM.

Research limitations/implications

The study provides implications and policy recommendations for the practicing managers and government agencies approaching the digital transformation towards the adoption of AI in the finance ecosystem.

Originality/value

The paper uses the systems approach for the development of the ISM of the enabling factors for the adoption of AI technology. On the basis of the results, the study proposes a policy framework to accelerate the functioning of the finance ecosystem with AI technology.

Artificial intelligence applications for sustainable solid waste management practices in Australia: A systematic review

Solid waste generation and its impact on human health and the environment have long been a matter of concern for governments across the world. In recent years, there has been increasing emphasis on resource recovery (reusing, recycling and extracting energy from waste) using more advanced approaches such as artificial intelligence (AI) in Australia. AI is a powerful technology that is increasingly gaining popularity and application in various fields. The adoption of AI techniques offers alternative innovative approaches to solid waste management (SWM). Although there are previous studies on AI technologies and SWM, no study has assessed the adoption of AI applications in solving the diverse SWM problems for achieving sustainable waste management in Australia. Moreover, there are inconsistencies and a lack of awareness on how AI technologies function in relation to their application to SWM. This study examines the application of AI technologies in various areas of SWM (generation, sorting, collection, vehicle routing, treatment, disposal and waste management planning) to enhance sustainable waste management practices in Australia. To achieve the aims of this study, prior studies from 2005 to 2021 from various databases are collected and analyzed. The study focuses on the adoption of AI applications on SWM, compares the performance of AI applications, explores the benefits and challenges, and provides best practice recommendations on how resource efficiency can be optimized to improve economic, environmental and social outcomes. This study found that AI-based models have better prediction abilities when compared to other models used in forecasting solid waste generation and recycling. Findings show that waste generation in Australia has been steadily increasing and requires upgraded and improved recovery infrastructure and the appropriate adoption of AI technologies to enhance sustainable SWM. Australia's adoption of AI recycling technologies would benefit from a national approach that seeks consistency across jurisdictions, while catering for regional differences. This study will benefit researchers, governments, policy-makers, municipalities and other waste management organizations to increase current recycling rates, eliminate the need for manual labor, reduce costs, maximize efficiency, and transform the way we approach the management of solid waste.

Machine learning techniques applied to mechanical fault diagnosis and fault prognosis in the context of real industrial manufacturing use-cases: a systematic literature review

When put into practice in the real world, predictive maintenance presents a set of challenges for fault detection and prognosis that are often overlooked in studies validated with data from controlled experiments, or numeric simulations. For this reason, this study aims to review the recent advancements in mechanical fault diagnosis and fault prognosis in the manufacturing industry using machine learning methods. For this systematic review, we searched Web of Science, ACM Digital Library, Science Direct, Wiley Online Library, and IEEE Xplore between January 2015 and October 2021. Full-length studies that employed machine learning algorithms to perform mechanical fault detection or fault prognosis in manufacturing equipment and presented empirical results obtained from industrial case-studies were included, except for studies not written in English or published in sources other than peer-reviewed journals with JCR Impact Factor, conference proceedings and book chapters/sections. Of 4549 records, 44 primary studies were selected. In 37 of those studies, fault diagnosis and prognosis were performed using artificial neural networks (n = 12), decision tree methods (n = 11), hybrid models (n = 8), or latent variable models (n = 6), with one of the studies employing two different types of techniques independently. The remaining studies employed a variety of machine learning techniques, ranging from rule-based models to partition-based algorithms, and only two studies approached the problem using online learning methods. The main advantages of these algorithms include high performance, the ability to uncover complex nonlinear relationships and computational efficiency, while the most important limitation is the reduction in model performance in the presence of concept drift. This review shows that, although the number of studies performed in the manufacturing industry has been increasing in recent years, additional research is necessary to address the challenges presented by real-world scenarios.

Human, Organisational and Societal Factors in Robotic Rail Infrastructure Maintenance

Robotics are set to play a significant role in the maintenance of rail infrastructure. However, the introduction of robotics in this environment requires new ways of working for individuals, teams and organisations and needs to reflect societal attitudes if it is to achieve sustainable goals. The following paper presents a qualitative analysis of interviews with 25 experts from rail and robotics to outline the human and organisational issues of robotics in the rail infrastructure environment. Themes were structured around user, team, organisational and societal issues. While the results point to many of the expected issues of robotics (trust, acceptance, business change), a number of issues were identified that were specific to rail. Examples include the importance of considering the whole maintenance task lifecycle, conceptualizing robotic teamworking within the structures of rail maintenance worksites, the complex upstream (robotics suppliers) and downstream (third-party maintenance contractors) supply chain implications of robotic deployment and the public acceptance of robotics in an environment that often comes into direct contact with passenger and people around the railways. Recommendations are made in the paper for successful, human-centric rail robotics deployment.

Antecedents and outcomes of artificial intelligence adoption and application in the workplace: the socio-technical system theory perspective

Purpose

The use of artificial intelligence (AI) in the workplace is on the rise. To help advance research in this area, the authors synthesise the academic research and develop research propositions on the antecedents and consequences of AI adoption and application in the workplace to guide future research. The authors also present AI research in the socio-technical system context to provide a springboard for new research to fill the knowledge gap of the adoption and application of AI in the workplace.

Design/methodology/approach

This paper summarises the existing literature and builds a theoretically grounded conceptual framework on the socio-technical system theory that captures the essence of the impact of AI in the workplace.

Findings

The antecedents of AI adoption and application include personnel subsystem, technical subsystem, organisational structure subsystem and environmental factors. The consequences of AI adoption and application include individual, organisational and employment-related outcomes.

Practical implications

A research agenda is provided to identify and discuss future research that comprises not only insightful theoretical contributions but also practical implications. A greater understanding of AI adoption from socio-technical system perspective will enable managers and practitioners to develop effective AI adoption strategies, enhance employees' work experience and achieve competitive advantage for organisations.

Originality/value

Drawing on the socio-technical system theory, the proposed conceptual framework provides a comprehensive understanding of the antecedents and consequences of AI adoption and application in the work environment. The authors discuss the main contributions to theory and practice, along with potential future research directions of AI in the workplace related to three key themes at the individual, organisational and employment level.

Technological Innovation, Sustainable Green Practices and SMEs Sustainable Performance in Times of Crisis (COVID-19 pandemic)

COVID-19 restrictions significantly affected SMEs, which have faced many challenges to their sustainability within this fragile new environment. This study proposes a holistic framework of sustainable performance by interrelating factors showing robust associations to produce this effect' for achieving sustainable performance in SMEs, through integrating the Technology Organisation Environment (TOE) and Resource Based View (RBV) models, to test how sustainable green practices can process the TOE factors when affecting sustainable performance. The research focuses on SMEs with worldwide employees and involves data collected from a range of different employees belonging to four different managerial levels. The process incorporated the analysis of 669 questionnaires to test the proposed hypotheses using structural equation modeling. Findings suggest that, together, TOE factors represent crucial inputs for green practices such as green training, green performance appraisal, that, in turn, mean critical processes lead to sustainable performance (output). Additionally, the findings should also inspire SMEs to focus even more effort on internal technological and organisational factors and to encourage an eco-friendly culture that would demand stakeholders adopt a more positive environmental stance.

Factors influencing green information technology adoption: A multi-level perspective in emerging economies context

Research in the area of green information technology (GIT) adoption is still sluggish and rather limited, particularly in the emerging economy context. To address this research void, this study investigates the determinants of GIT adoption in the workplace at the individual and organizational levels using an integrated framework that combines the “technology-organization-environment” (TOE) framework, the “technology readiness index” (TRI), and social psychology theories. Data is collected via paper-based survey from different organizations in the United Arab Emirates. Structural equation modelling was utilized to test the hypotheses that were presented in our model. The findings show that the integrated model has good explanatory power and confirms its robustness in predicting the GIT adoption. Organizational factors comprising management support, resource commitment, and quality of human resources have emerged as strong determinants of GIT adoption. Individual factors, on the contrary, demonstrated weak influence on GIT adoption. This study is one of the first empirical attempts that predict GIT adoption in the United Arab Emirates context. The paper concludes with several implications that can foster GIT adoption initiatives, particularly for emerging economies.

Drivers and outcomes of green information technology adoption in service organizations: an evidence from emerging economy context

Purpose

This paper aims to examine the technology-organization-environment (TOE) predictors of green information technology adoption in an emerging economy, namely, the United Arab Emirates (UAE) and their impact on work performance among UAE organizations.

Design/methodology/approach

A paper-based survey was carried out by engaging employees in different organizations in the UAE. The “partial least squares” (PLS) method was used to test and analyze the measurement and the structural research models.

Findings

The analysis shows support to all the hypotheses, with the exception of the influence of competitive force.

Originality/value

The results can be valuable for practitioners and decision-makers in the emerging economy context as the results will help them validate their adoption decisions and effectively contribute to sustainability strategies.

Mobile apps use for wellness and fitness and university students’ subjective wellbeing

Subjective wellbeing among mobile application users attracted researchers’ interest in recent years due to its prevalent role in enhancing everyday life, particularly during the recent coronavirus pandemic (COVID-19). While previous work has primarily focused on users’ intention to adopt mobile apps for wellness and fitness (MAWF) purposes, scarce attention has been paid to the post-adoption impact of these apps on users’ subjective wellbeing. This study empirically integrates ‘technology readiness’ and ‘technology acceptance’ models (TRAM) to predict subjective wellbeing among MAWF users. It also critically assesses the strength of the mediating effects on the link between technology readiness and subjective wellbeing. Data analysis of 694 actual users of MAWF by means of SEM-PLS approach proves the robust power of the TRAM model in predicting subjective wellbeing. In addition to their mediating effects, technology acceptance constructs tend to be more influenced by positive dimensions (i.e., optimism and innovativeness) than that of negative dimensions (i.e., insecurity and discomfort) of technology readiness. This study is one of the first attempts to predict subjective wellbeing among actual users of MAWF. The study also delineates a broad spectrum of implications that enrich existing research and better inform decision makers in mobile health field.

Examining the Adoption of Onlineto- Offline (O2O)

The online-to-offline (O2O) business model is rapidly growing among organizations, yet current knowledge on O2O adoption is predominantly individual focused, with little research on organizational adoption and the factors driving adoption. To address this gap, underpinned by the diffusion of innovation (DOI) theory, this study collected qualitative data (24 semistructured interviews), which were analyzed using content analysis techniques. We found that offline service quality and social network prosperity are some of the factors driving O2O adoption. Surprisingly, inefficient offline marketing was also found to drive O2O adoption, which indicates new challenges posed by the growing online business environment. We found that not all factors can be categorically classified as facilitating or impeding adoption, as some factors (such as operational challenges and costs) could play dichotomous roles of facilitating or impeding in the context of peculiar circumstances. For example, we found cost to be an impeding factor, yet the results also indicated the benefits of cost reduction resulting from O2O adoption, thereby rendering cost a contentious issue. This study extends the application of DOI theory to the O2O adoption stage, and identifies a number of new factors associated with internal/external organizational characteristics, as postulated in the DOI. Managerial implications are discussed.

Internet of Things (IoT) Implementation in Learning Institutions: A Systematic Literature Review

Internet of Things (IoT) is a computing concept facilitating the management of collaborative activities from one central area. Millennial learners, growth in enrolment numbers in universities, and the need for equity and quality learning necessitate the use of IoT technologies in education. The focus of this paper is to examine IoT implementations in learning institutes, their application areas, the themes presented, the models and methodologies used, and the benefits. This study concentrated on publications from 2008 to 2017. The outcomes revealed that the utilization of IoT for tracking and tracing a learner’s attendance had been one of the application areas of IoT in education. This study further categorized the papers and presents novel research opportunities based on concentrated themes and areas that had not been fully exhausted. Most research studies employed qualitative methods, with a few utilizing a quantitative approach with surveys. Research themes exhibited a shortcoming in other important themes, such as the models and methodologies used for implementing IoT. Finally, the results of this study agree that IoT implementation could help solve some issues in learning institutions like equity and quality learning. The results from this research also provide a base for future research works on the successful implementation of IoT in learning institutions.

Ready or Not, AI Comes— An Interview Study of Organizational AI Readiness Factors

Artificial intelligence (AI) offers organizations much potential. Considering the manifold application areas, AI’s inherent complexity, and new organizational necessities, companies encounter pitfalls when adopting AI. An informed decision regarding an organization’s readiness increases the probability of successful AI adoption and is important to successfully leverage AI’s business value. Thus, companies need to assess whether their assets, capabilities, and commitment are ready for the individual AI adoption purpose. Research on AI readiness and AI adoption is still in its infancy. Consequently, researchers and practitioners lack guidance on the adoption of AI. The paper presents five categories of AI readiness factors and their illustrative actionable indicators. The AI readiness factors are deduced from an in-depth interview study with 25 AI experts and triangulated with both scientific and practitioner literature. Thus, the paper provides a sound set of organizational AI readiness factors, derives corresponding indicators for AI readiness assessments, and discusses the general implications for AI adoption. This is a first step toward conceptualizing relevant organizational AI readiness factors and guiding purposeful decisions in the entire AI adoption process for both research and practice.

A review of challenges and opportunities of blockchain adoption for operational excellence in the UK automotive industry

Purpose

This paper aims to explore the challenges and opportunities of blockchain technology adoption from the lens of the technological–organisational–environmental (TOE) framework for operational excellence in the UK automotive industry context.

Design/methodology/approach

The research methodology of this study follows a systematic review approach, which analyses existing academic published research papers in the top 35 academic journals. There was no specific timeframe established for this study and shortlisting the articles through a set of used keywords. A sample of 71 articles was shortlisted and analysed to provide a discussion on technological and management challenges and opportunities of blockchain adoption from the lens of the TOE framework for operational excellence.

Findings

The findings of this study present significant theoretical and managerial implications and deep understanding for firms seeking to understand the challenges and opportunities of blockchain adoption for their operational excellence.

Research limitations/implications

The systematic literature approach was considered for the present study to explore existing academic papers on technological and management challenges and opportunities from the lens of TOE framework for operational excellence, whereas a more specified method meta-analysis can be considered for future research. The study has been explored in the UK automotive industry context, which has been considered as the limitation of generalisation across countries and industries.

Originality/value

This paper represents the most comprehensive literature study related to the technological and management challenges and opportunities of blockchain from the TOE framework angle for operational excellence.

Factors Influencing the Realization of Competitive Advantage in the Private Portals Context

The aim of this study is to empirically explore the influences of a set of key technological, organizational, and environmental (TOE) factors on the achievement of a strategic promised benefit of private portals, which is competitive advantage. Such exploration has not received attention in the web-based information systems’ area. To explore these influences, a theoretical model was developed on the basis of the information system adoption’s literature. The model postulates the TOE factors as crucial antecedents to the realization of competitive advantage. To validate the theoretical model, a questionnaire was constructed by focusing on the most precise measurements items for the TOE factors. A total of 241 responses were collected from the private portal’s users in a higher education institution in Saudi Arabia. The structural equation modeling approach was applied for conducting the required assessment. The results demonstrate that among the tested TOE factors, the relative advantage of private portals and the competitive pressure to adopt them have positive impacts on the achievement of competitive advantage. The empirical evidences produced by this study provide more clarifications about the factors that should be managed carefully to gain competitive advantage from the adopted information system innovations.

Adoption of Automatic Warehousing Systems in Logistics Firms: A Technology–Organization–Environment Framework

The adoption of automatic warehousing systems, a type of green technology, has been an emerging trend in the logistics industry. In this study, we develop a conceptual model using a technology–organization–environment framework to investigate the factors which influence logistics firms to adopt green technology. Our model proposes that the adoption of green technology is influenced by perceived advantage, cost, technological turbulence, business partner influence, firm size, firm scope and operational performance. The objective of this study is to identify the conditions, as well as the contributing factors, for the adoption of automatic warehousing systems in logistics firms. Data were collected from 98 firms in China, and structural equation modeling with partial least squares is adopted to analyze the data. The results suggest that high perceived relative advantage, firm size, cost, firm scope, operation performance, technological turbulence and influence of business partners are important factors affecting IT adoption in small businesses. Therefore, decision support should be provided for enterprises from the three aspects of technology, organization and environment to improve the adoption of automatic warehousing systems.

Big data analytics adoption model for small and medium enterprises

Purpose

Big data analytics (BDA) is recognized as a turning point for firms to improve their performance. Although small- and medium-sized enterprises (SMEs) are crucial for every economy, they are lagging far behind in the usage of BDA. This study aims to provide a single and unified model for the adoption of BDA among SMEs with the integration of the technology–organization–environment (TOE) model and resource-based view.

Design/methodology/approach

A survey of 112 manufacturing SMEs in Iran was conducted, and the data were analysed using structural equation modelling to test the model of this study.

Findings

The results offer evidence of a BDA mediation effect in the relationship between technological, organizational and environmental contexts, and SMEs performance. The findings also demonstrated that technological and organizational elements are the more significant determinants of BDA adoption in the context of SMEs. In addition, the result of this study confirmed that BDA adoption could enhance the financial and market performance of SMEs.

Practical implications

Providing a single unified framework of BDA adoption for SMEs enables them to appreciate the importance of most influential elements (technology, organization and environment) in the adoption of BDA. Also, this study may encourage SMEs to be more willing to use BDA in their businesses.

Originality/value

Although there are studies on BDA adoption and firm performance among large companies, there is a lack of empirical research on SMEs, in particular, based on the TOE model. SMEs differ from large companies in terms of the availability of resources and size. Therefore, this study aimed to initiate a conceptual framework of BDA adoption for SMEs to assist them to be able to take advantage of the adoption of such technology.

Understanding the determinants of GIT post-adoption: perspectives from Mozambican institutions

This study aims to understand the determinants of geographical information technologies at the scale of post-adoption use and intention to increase the level of use in Mozambican institutions. Three known theories (diffusion of innovation theory, technology - organisation - environment framework, and institutional theory) have been used in order to accomplish the study. The data analysis showed that the variables compatibility, geographical scope, expansion opportunities, and normative pressure contribute to explaining GIT use. Relative advantage, complexity, coercive pressure, and mimetic pressure contribute to explaining the intention to increase GIT levels of use. The model revealed substantial power of explanation for GIT post-adoption.

Social customer relationship management factors and business benefits

Purpose

This study aims to identify the business benefit of and factors affecting the use of social customer relationship management (SCRM) in Indian organizations.

Design/methodology/approach

Building on theoretical foundations, a conceptual model of factors affecting SCRM in Indian organizations is developed and empirically tested through a survey and corresponding analysis using SPSS and AMOS software.

Findings

The study presents empirical evidence that technological competence, environmental characteristics and organizational environment positively impact the actual use of SCRM on Indian organizations. Additionally, leadership support of organizations impacts positively the actual use of SCRM in organizations, while the trust factor insignificantly impacts the latter. The actual use of SCRM in organizations was found to have a positive impact on their business benefits.

Research limitations/implications

The theoretical model is built on the constructs of the technology, environment and organizational framework. It has added new factors, such as leadership support and trust, and thereby identified the business benefits of organizations using SCRM mediating through the organizations’ actual use of SCRM. The proposed model is simple, implementable and has a high explanative power of 81 per cent.

Practical implications

The study provides practitioners with evidence and practicable knowledge regarding the means and impact/benefits of SCRM use in Indian organizations.

Originality/value

The study is one of few empirical studies on the topic and contributes valuable knowledge to extant works through additional factors, theoretical conceptualization and empirical scientific findings of both scholarly and executive worth.

Organizational Performance and Sustainability: Exploring the Roles of IT Capabilities and Knowledge Management Capabilities

This study explores the effects of organizational information technology (IT) capability in determining organizational performance and sustainable competitive advantage. Building on the resource-based and knowledge-based views of a firm, the study proposes a theoretical framework. In this framework, organizational IT capability is theorized to strengthen organizational performance and sustainable competitive advantage, directly and indirectly, through organizational knowledge management capabilities. Data collected from the middle and senior managers of diverse organizations in an emerging economy have been used to test the relationships in the framework. To estimate the proposed relationships in the conceptual model, we use structural equation modeling through SmartPLS 3.2. The results confirm that organizational IT capability significantly impacts organizational performance and sustainable competitive advantage. Additionally, organizational knowledge management capabilities partially mediate the relationship between IT capability and the outcomes (i.e., organizational performance and sustainable competitive advantage). The study concludes with a discussion of the implications for academicians and managers.

Impacts of computerized maintenance management system and relevant supportive organizational factors on total productive maintenance

Purpose

The application of automated systems is rapidly increasing in different industries and organizations. In this regard, computerized maintenance management systems (CMMS) using information technology play an important role in the automating production systems. The purpose of this paper is to investigate the impacts of CMMSs and relevant supportive organizational factors on the effectiveness of total productive maintenance.

Design/methodology/approach

This study is classified as a quantitative survey-based research using structural equation modeling. The scope of the study includes manufacturing companies in Iran. A total of 125 questionnaires from 60 companies were collected from January to March 2014 to help validate the conceptual model and test the hypotheses.

Findings

The results support the concept CMMSs positively relates to relevant supportive organizational factors (resource allocation, decision-making structure, senior management support, employees’ involvement and effective instruction) on the effectiveness of total productive maintenance. The relevant supportive organizational factors can also be seen as the predictors of CMMSs.

Originality/value

This study integrates the CMMSs and relevant supportive organizational factors in a robust model to examine the effectiveness of total productive maintenance. This study also examines the impacts of CMMSs and relevant supportive organizational factors on total productive maintenance which seems to not be done previously.

RFID application in patient and medical asset operations management: A technology, organizational and environmental (TOE) perspective into key enablers and impediments

PURPOSE

In spite of the recent progress in understanding how radio frequency identification (RFID) systems can substantially advance health care service, there is a significant gap in the literature concerning determinants of RFID application in managing various forms of health care operations. Hence, this study attempts to fill this gap by examining the key enablers and impediments of using RFID systems in patient and medical asset operations management using the technology, organization and environment framework (TOE).

METHODS

A research model was developed using a variety of TOE factors that may enable or impede RFID adoption in managing health care operations. Then, the model was empirically tested by means of Structural Equation Modelling (SEM) based on survey data of 311 online questionnaire responses that were collected from managers, technicians, physicians and nurses in charge of asset and patient management in public and private hospitals in the United Arab Emirates. The majority of respondents were over 30 years old (63%) and have more than 5 years of experience in the medical context (88%). They work mainly in private hospitals (71%) in managerial positions (65%). This profile designates sufficient experience and knowledge of participants to understand the questions.

RESULTS

The findings demonstrate the effect of technical advantages and organizational capacity on both asset and patient management is significant, while the effect of environmental competitiveness is only evident in patient management operations. Furthermore, the results confirm the negative influence of technical complexity and environmental uncertainty on both asset and patient management. Surprisingly, using RFID in asset and patient management tend to be not influenced by organizational resistance. The paper proposes a number of implications that can guide leaders and vendors to successfully implement RFID technology for managing healthcare operations. It directs the attention of RFID research toward future venues within the health care context.

CONCLUSIONS

Hospitals must contemplate the impact of technological, organizational and environmental forces to leverage the benefits of RFID in patient and asset operations management. The results of SEM confirmed the strong effect of the variables on patient management since 57 per cent of its variance is explained by five factors (i.e., technical advantages, organizational capacity, environmental competitiveness, technical complexity and environmental uncertainty). Four factors explain about 48 per cent of the variance in asset management (i.e., technical advantages, organizational capacity, technical complexity and environmental uncertainty). The results provide robust implications for health care managers and RFID vendors to better understand crucial RFID implementation issues, increase its technology fit into service operations, and accelerate its implementation as follows: (1) while organizational resistance does not show significant impact on RFID adoption for managing patient and asset operations, health care professionals should consider that RFID implementation decision is mainly organizational at the firm level rather than an individual choice, as long as RFID benefits are well communicated to the staff. (2) while the effect of environmental competitiveness is only evident in using RFID in managing patient operations, health care professionals should focus on RFID applications that have direct impact on enhancing health service quality, flexibility and delivery considering patients as a base for competitiveness; (3) with regard to the impact of technical advantages, RFID benefits such as enhancing work efficiency and reducing cost should be documented, communicated and nurtured to medical and administrative employees; (4) In response to the impact of organizational capacity, the contribution of RFID applications to medical and managerial knowledge generation and utilization should be tracked and integrated into daily work processes; (5) Vendors should provide appropriate orientations and training sessions targeting RFID complexity involving networks, architectures and operating; and (6) the customization of commercial RFID technology for managing health service operations must be deliberated between all stakeholders in health care context. Forthcoming research is needed to reexamine this model with different variables (e.g., culture) and under further health care conditions or contexts.

ERP System Adoption Analysis Using TOE Framework in Permata Hijau Group (PHG) Medan

In this research, employee adoption intention is important consideration of successful ERP system implementation. The purpose of this research is to identify the important factors in Technology-Organization-Environment framework that affect ERP system adoption's intention. Online survey data were collected from 175 employees with active status from each department who had used ERP in PHG, Indonesia. The research data was collected through simple random sampling method and applying SEM in AMOS 24. The results of this article proves that technology readiness, organization size, and external support significantly influence ERP system adoption intention. Compatibility, relative advantage, complexity, top management support, business operation, and competition pressure have no significant influence on ERP system adoption intention. Thus, it can be concluded that ERP system adoption's intention is important to enhance corporate competitive advantage. Adopted ERP system can be developed continuously by involving employees to achieve information technology and business strategy within company.

eReadiness of public university libraries in Malawi to use mobile phones in the provision of library and information services

Purpose

The purpose of this paper is to present findings of a study conducted to determine eReadiness status of public university libraries in Malawi to use mobile phones in the provision of library and information services.

Design/methodology/approach

The researcher carried out in-depth semi-structured interviews with university/college librarians and information and communications technology (ICT) directors using interview guides. Students were also administered with a survey questionnaire that contained closed- and some open-ended questions. Proceedings of the interviews were recorded using a tape recorder whilst backup notes were recorded in a notebook. Qualitative data were transcribed and analysed using NVivo software whilst quantitative data were analysed using SPPS.

Findings

The study findings revealed that institutions studied had the ICT infrastructure necessary for offering library and information services on the mobile phone platform. Moreover, students had mobile phones which were connected to internet to facilitate their access to services offered. However, the institutions covered by this study did not have operational ICT policies to govern the operations of library and information services offered through mobile phones although draft ICT policies were available. The study further concluded that though the human resources required to manage the provision of library and information services through mobile phones in the institutions studied were available, they did not have the necessary skills and numbers to provide quality services. Other findings revealed that attitudes of library staff and students to the offering and access to services through mobile phones were positive. The study also revealed that there are some factors that could impact the offering of library services through mobile phones.

Research limitations/implications

Although Malawi has four public universities, this study only focused on three of them. Moreover, academic staff is another important user group of academic libraries. In this case, findings reported in this paper only focus on students. This implies that library’s readiness to offer services through mobile phones to this group remains unknown hence may have to be covered by future studies. Much as the study incorporated a quantitative strand in addition to the qualitative one, it neither involved theory testing nor confirmation as is the case with other related studies. This implies that the two theories used in this study (the unified theory of acceptance and use of technology and the technology-organisation-environment) were not used in the strict sense, which is empirical at the core, but rather to put the problem studied in the context of other related studies.

Practical implications

The findings have practical implications in that they can be used for planning the implementation of library and information services through mobile phones in public university libraries in Malawi. Other related institutions can also use the findings as a reference point in planning the implementation of similar services.

Originality/value

Studies relating to the use of mobile phones in the delivery of library and information services have not been conducted in public universities in Malawi. Findings of this study will, therefore, inform researchers intending to conduct similar or related studies not only in public universities in Malawi but other related institutions as well.

Understanding Intentions to Switch Toward Cloud Computing at Firms' Level

This research aims to study intentions to switch toward cloud computing at firms' level. As a new way to deploy information technologies (IT) within firms, switching toward cloud computing remains a hard decision that depends on several contextual factors. While several studies have focused mainly on technological aspects, this research adopts a multidimensional perspective by combining the Technology-Organization-Environment (TOE) framework with a two-factor theory perspective. Doing so, the authors attempt to propose a research model that can be useful to deeply understand how firms perform when thinking about switching toward cloud-based solutions. A multiple-case study within five Tunisian firms has been conducted to contextualize the research model and give it more explanation power. The Tunisian context should be interesting, as cloud computing adoption is a new topic that is not sufficiently studied in developing countries, particularly in those characterized by an economy in transition. Data have been collected by semi-structured interviews and coded using the Nvivo software. The analysis of interviews content shows that the expected switching benefits and risks play a mediating role between TOE factors and intentions to switch toward cloud computing. Indeed, the authors found some different results within cases revealing the dual effects of technology, organization, and environment factors on intentions by generating different expected switching benefits and risks. In light of these results, some recommendations are proposed to decision makers in this area.

Integrated technology-organization-environment (T-O-E) taxonomies for technology adoption

Purpose

The T-O-E framework enjoys robust scholarly accolade but it rarely espouses clearly task and individual factors. Although task and individual contexts had been separately addressed by task-technology-fit (TTF) and unified theory of acceptance and use of technology (UTAUT), respectively, the purpose of this paper is to complement and/or extend the T-O-E’s insights by integrating TTF and UTAUT frameworks, and developing and empirically testing a 12-factor framework that spans five contexts.

Design/methodology/approach

Survey data were proportionally collected from six groups of small service enterprises with strong operations in Port Harcourt, Nigeria and the mode of sampling was purposive and snow-ball while analysis involved logistic likelihood regression.

Findings

The relationship between adoption and the factors within the contexts of technology, organization, environment and task were statistically supported though some had negative coefficients. For individual context, social factor had a statistically significant negative coefficient but hedonistic drive was not statistically supported.

Research limitations/implications

The study is limited by its scope of coverage; therefore, extended data are needed to apply the findings to other sectors/industries and to factor in the implementation and post-adoption phases and business-to-business adoption in order to forge a more integrated and holistic adoption framework.

Practical implications

The findings encourage vendors and policy makers to place more premiums on organizational and task factors than on technological, environmental and individual factors and to craft informed marketing programs that would appeal to actual and potential adopters and cause them to progress in the loyalty ladder.

Originality/value

This paper contributes to the growing research on technology adoption; it uses factors within the T-O-E, TTF and UTAUT frameworks to explain adoption of technologies and to establish the underlying relationships amongst T-O-E factors through integrating other useful frameworks.

Critical Factors Influencing Decision to Adopt Human Resource Information System (HRIS) in Hospitals

The aim of this research is to explore factors influencing the management decisions to adopt human resource information system (HRIS) in the hospital industry of Bangladesh-an emerging developing country. To understand this issue, this paper integrates two prominent adoption theories-Human-Organization-Technology fit (HOT-fit) model and Technology-Organization-Environment (TOE) framework. Thirteen factors under four dimensions were investigated to explore their influence on HRIS adoption decisions in hospitals. Employing non-probability sampling method, a total of 550 copies of structured questionnaires were distributed among HR executives of 92 private hospitals in Bangladesh. Among the respondents, usable questionnaires were 383 that suggesting a valid response rate of 69.63%. We classify the sample into 3 core groups based on the HRIS initial implementation, namely adopters, prospectors, and laggards. The obtained results specify 5 most critical factors i.e. IT infrastructure, top management support, IT capabilities of staff, perceived cost, and competitive pressure. Moreover, the most significant dimension is technological dimension followed by organisational, human, and environmental among the proposed 4 dimensions. Lastly, the study found existence of significant differences in all factors across different adopting groups. The study results also expose constructive proposals to researchers, hospitals, and the government to enhance the likelihood of adopting HRIS. The present study has important implications in understanding HRIS implementation in developing countries.

Technological, organisational and environmental factors influencing managers’ decision to adopt cloud computing in the UK

Purpose

– The purpose of this paper is to determine the factors influencing managers’ decision to adopt cloud computing in the UK using the “Technology-Organisation-Environment” (TOE) framework.

Design/methodology/approach

– Data were collected through a self-created questionnaire based survey that was completed by 257 mid-to-senior level decision-making business and information technology (IT) professionals from a range of UK end-user organisations. The derived hypotheses were tested using various data analysis techniques including principal component analysis and logistic regression.

Findings

– The results show that four out of the eight factors examined have a significant influence on the adoption decision of cloud computing services in the UK. Those key factors include competitive pressure, complexity, technology readiness and trading partner pressure. The latter predictor; trading partner pressure, was the most significant factor for the adoption decision of cloud services reflecting organisations’ concerns on legal regulations, co-creation and customisation, service linkage and vendor locking which adds complexity to the process of selecting an appropriate vendor.

Research limitations/implications

– This research found trading partners (cloud service providers) significantly influence managers’ decisions to adopt cloud services, however, further research is required to fully understand all the aspects involved especially with the growing number of vendors available. Although over 250 usable responses to the questionnaire were received and analysed, there was not a sufficient quantity of responses from each industry sector or organisation size to conduct further analysis.

Practical implications

– The findings reveal the important role of cloud computing service providers to enable end-users to better evaluate the use of cloud computing. It also reveals that top management support is no longer a driver as organisations are starting to adopt cloud computing services on the basis of cheaper and more agile IT resources in order to support business growth.

Originality/value

– This research provides original insight for cloud computing adoption within the UK from a managerial perspective.