Technology Organization Environment Research Articles

Development of an augmented reality remote maintenance adoption model through qualitative analysis of success factors

In recent decades, engineering manufacturers have increasingly adopted servitization strategies, making efficient maintenance service delivery a key corporate activity for revenue growth and profitability. Recently, augmented reality remote maintenance (ARRM) has become available and promises service delivery efficiency gains, which is why engineering manufacturers are starting to adopt it. Therefore, the purpose of this paper is to analyze the promoting and inhibiting factors of ARRM adoption in support of industrial service delivery. To this end, a qualitative explorative approach based on the technology–organization–environment (TOE) framework has been deployed. Data were collected from a systematic literature review and an empirical interview study with 16 companies. In total, 38 interviewees from different hierarchical levels participated in the interview study. Based on a thematic analysis, this paper provides a novel ARRM adoption model and contributes six technological, seven organizational, and four environmental adoption success factors. The promoting factors are ARRM key features, qualitative operational advantages, quantitative operational advantages, value proposition, value creation network, finance, image, adoption management, resource allocation, strategic realignment, skills gap, and governmental regulation; further, augmented reality user experience, data connection, information provision, intellectual property protection, and remote service acceptance were identified as inhibiting factors. This paper qualifies as the first attempt to consolidate engineering-focused ARRM literature with respect to remote service delivery, adding the industrial adoption perspective and elaborating on the impact of the inter-organizational nature of ARRM technology on industrial adoption. Thus, this research contributes to the transition from pure engineering research to industrial ARRM adoption research.

ZAKAT, INFAQ AND SHADAQAH (ZIS) DIGITALIZATION: A CASE STUDY USING TECHNOLOGY ORGANIZATION ENVIRONMENT FRAMEWORK

Technological disruption has changed the process of collecting zakat, infaq, and shodaqoh (ZIS). These changes can pose both threats and opportunities for ZIS institutions. This study aims to describe the acceptability of ZIS institutional technology from a Technology-Organization-Environment (TOE) perspective. This research is qualitative research with a case study approach. This study uses a data collection method consisting of observation, in-depth interviews, and documentation. Using in-person interviews and via cell phone. The subject of this research is the head of the ZIS institution. The results of the study state that all ZIS institutions have made technological innovations in collecting zakat, infaq, and shodaqoh. The existence of limited human resources and organizations' low acceptance of digital platforms are obstacles to not maximizing digital platforms' use. Strong encouragement from muzakki, government, and digital platform-based ZIS institutions has inspired them to develop technological innovations that suit their needs. This research contributes practically to ZIS institutions that the map of muzakki and donors has begun to change so that technological readiness is the key to the sustainability of ZIS institutions.

Utilisation of drones in achieving various applications in smart warehouse management

PurposeOrganisations and industries are often looking for technologies that can accomplish multiple tasks, providing economic benefits and an edge over their competitors. In this context, drones have the potential to change many industries by making operations more efficient, safer and more economic. Therefore, this study investigates the use of drones as the next step in smart/digital warehouse management to determine their socio-economic benefits.Design/methodology/approachThe study identifies various enablers impacting drone applications to improve inventory management, intra-logistics, inspections and surveillance in smart warehouses through a literature review, a test of concordance and the fuzzy Delphi method. Further, the graph theory matrix approach (GTMA) method was applied to ranking the enablers of drone application in smart/digital warehouses. In the subsequent phase, researchers investigated the relation between the drone application's performance and the enablers of drone adoption using logistic regression analysis under the TOE framework.FindingsThis study identifies inventory man agement, intra-logistics, inspections and surveillance are three major applications of drones in the smart warehousing. Further, nine enablers are identified for the adoption of drone in warehouse management. The findings suggest that operational effectiveness, compatibility of drone integration and quality/value offered are the most impactful enablers of drone adoption in warehouses. The logistic regression findings are useful for warehouse managers who are planning to adopt drones in a warehouse for efficient operations.Research limitations/implicationsThis study identifies the enablers of drone adoption in the smart and digital warehouse through the literature review and fuzzy Delphi. Therefore, some enablers may be overlooked during the identification process. In addition to this, the analysis is based on the opinion of the expert which might be influenced by their field of expertise.Practical implicationsBy considering technology-organisation-environment (TOE) framework warehousing companies identify the opportunities and challenges associated with using drones in a smart warehouse and develop strategies to integrate drones into their operations effectively.Originality/valueThis study proposes a TOE-based framework for the adoption of drones in warehouse management to improve the three prominent warehouse functions inventory management, intra-logistics, inspections and surveillance using the mixed-method.

Barriers to continuance use of cloud computing: Evidence from two case studies

Continuous use of cloud computing and cloud sourcing has received limited research attention compared to cloud adoption. There are indications that cloud sourcing benefits are not easy to reap in continuous use for companies, calling for more research on the continuance use of cloud computing. The current study is one of the first studies of the continuance use of cloud computing processes at the organizational level, contributing to the management and business research literature on cloud computing. In particular, the present study has contributed with two case studies verifying the existence of barriers and more importantly identifying an additional type of barrier: management process barriers (MP), i.e., lack of objectives and strategies for cloud sourcing and lack of organizing cloud vendor communication. Overcoming or reducing management process barriers guides the continuance use of cloud computing process in a strategic direction for the company and enables cloud-related innovation. As a contribution, our research builds on and extends extant research by providing a TOMPE framework of barriers to the continuance use of cloud computing (based and modified from the technology–organization–environment (TOE) framework, by complementing it with the identified management process barriers).

Determinants of Software as a Service (SaaS) Adoption

ABSTRACT The extant literature on software as a service (SaaS) adoption has largely leveraged traditional and general factors identified in existing information system literature to examine determinant factors that affect firms’ adoption decisions. Anchoring our study in the technological-organizational-environmental (TOE) framework and following insights from information technology (IT) outsourcing literature, we examine determinants of SaaS adoption through a contextualized lens of technological, organizational, and environmental contexts. In particular, we hypothesize that firm performance and IT department size negatively affect SaaS adoption, while competitor adoption positively affects SaaS adoption. Our empirical analysis using a sample of 1,062,128 small and medium firm observations over 9 years supports the hypotheses. We discuss the implications that our findings have for research and practice.

A Hybrid Evaluation Model for e-Learning Platforms Based on Extended TOE Framework

E-learning platforms (ELPs) are revolutionizing the higher education system, as they offer tremendous potential to fulfill instructional plans, safeguard students’ learning rights, and improve teaching quality. Higher education institutions (HEIs) have to consider the selection of ELPs from an organizational perspective, which involves multiple stakeholders like university administrators, students, and educators. Therefore, one can take the ELP selection as a complex multi-criteria decision-making (MCDM) problem. This research proposes a new hybrid MCDM approach on the basis of the fuzzy analytic hierarchy process (FAHP) and the evaluation based on distance from the average solution (EDAS) method to select the best ELPs. First, from the organizational perspective, we extend the technology-organization-environment (TOE) framework by adding an auxiliary resource (AR) dimension and define and prioritize 4 criteria and 14 criteria for evaluating and selecting ELPs. Second, the study uses the fuzzy set theory to process the language evaluation of experts, the FAHP method to determine criteria and sub-criteria weights, and EDAS to rank the alternatives. Finally, based on the importance-performance analysis (IPA) method, we identify the most appropriate strategic options for enhancing competitiveness. Three practical cases of China’s ELP evaluation validate the proposed model’s applicability and superiority by comparing to the two other classic evaluation models. In addition, through analysis, we obtain some encouraging results that provide some references for universities to formulate ELP selection policies and offer suggestions for platform producers to further optimize the design.

Influence of big data adoption on sustainable marketing and operation of SMEs: a hybrid approach of SEM-ANN

PurposeThis research aimed to analyze and prioritize the factors affecting sustainable marketing (SM) and sustainable operation (SO) of manufacturing small and medium-sized enterprises SMEs through big data adoption (BDA).Design/methodology/approachThe technology-organization-environment (TOE) framework was used as a theoretical base and data were gathered from manufacturing SMEs in Malaysia. The 159 questionnaire replies of chief executive officer (CEO)/managers were analyzed using a hybrid approach of structural equation modeling-artificial neural network (SEM-ANN).FindingsThe findings of this study showed that perceived benefits (PB), technological complexity (TC), organization's resources (OR), organization's management support (OMS) and government legislation (GL) are the factors that influence BDA and promote SM and SO. The findings of ANN showed that a perceived benefit is the most important factor, followed by OMS.Practical implicationsThe findings of this study can assist SMEs managers in making strategic decisions and improving sustainable performance and thus contribute to overall economic development.Originality/valueThe manufacturing industry is under immense pressure to integrate sustainable practices for long-term success. BDA can assist industries in aligning industries' operational capabilities. The majority of the current research have mainly emphasized on BDA in corporations. However, the associations between BDA and sustainable performance of manufacturing SMEs have been less explored. To address this issue, this study developed a theoretical model and examined the influence of BDA on SM and SO of manufacturing SMEs. Meanwhile, the hybrid methodological approach can help to uncover both linear and non-linear relationships better.

Do supply chain related factors enhance the prediction accuracy of blockchain adoption? A machine learning approach

This study employs a machine learning approach to examine whether and to what extent supply chain related factors can improve the prediction accuracy of blockchain technology (BT) adoption. The supply chain factors studied include supply chain collaboration, information sharing along the supply chain, partner power, trust in supply chain partners and Guanxi with supply chain partners. We choose the Technology-Organization-Environment (TOE) framework as the benchmark model and quantify the importance of supply chain factors by comparing the prediction accuracy of the benchmark model using only the TOE framework with an extended model combining supply chain factors with the TOE framework. Based on data collected from 629 Chinese firms, we find that Support Vector Machine stands out among all machine learning algorithms: the complete model including both supply chain and TOE factors reaches an accuracy rate of 89.3 %, while the model including only TOE factors has an accuracy rate of 83 %. Based on a 10-fold cross-validated paired t-test, we further confirm that incorporating supply chain factors can significantly improve the prediction accuracy by 6.34 % over the benchmark model. Our results indicate that TOE factors are insufficient to understand and predict BT adoption; supply chain factors also need to be considered.

Study on the Influencing Factors of Digital Transformation of Construction Enterprises from the Perspective of Dual Effects—A Hybrid Approach Based on PLS-SEM and fsQCA

The digital transformation of Chinese construction enterprises is crucial for achieving sustainable and high-quality development in the construction industry. However, there is still a lack of in-depth research on the impact mechanism of digital transformation in construction enterprises. The purpose of this study is to explore the multiple influencing factors and complex causal relationships of digital transformation in construction enterprises and promote the deep integration of digitalization and construction enterprises. To this end, based on the dual-effect perspective (net effect perspective of a single influencing factor and configuration effect perspective of multiple influencing factors), using the “technology–organization–environment” framework (TOE framework) to construct a research model of influencing factors for digital transformation in construction enterprises. A sample of 236 construction enterprise managers was surveyed, and partial least squares structural equation modeling (PLS-SEM) and fuzzy set qualitative comparative analysis (fsQCA) methods were used to empirically analyze the dual effects of influencing factors for digital transformation in construction enterprises. The results show that: (1) from the net effect perspective, there are seven factors that significantly impact digital transformation in construction enterprises; (2) from the configuration effect perspective, there are three paths that can achieve high-level digital transformation in construction enterprises, and one path that leads to low-level digital transformation; (3) from the dual-effect perspective, top management support and policy support are key factors for digital transformation in Chinese construction enterprises. The research results enrich the relevant research on digital transformation in construction enterprises and provide a reference basis for promoting digital transformation in construction enterprises.

The critical determinants impacting artificial intelligence adoption at the organizational level

This study aims to investigate the main technological and socio-environmental factors influencing the adoption intentions with regard to AI-based technologies at the organizational level. A conceptual model based on innovation diffusion theory (DOI) and the technology-organization-environment (TOE) framework is proposed and tested empirically using survey-based data collected from 512 senior IT/IS managers in public/private organizations located in Jordan. The results indicate that relative advantage, top management support, cost-effectiveness, competitive pressure, vendor support, compatibility, AI strategic alignment and availability of resources, positively influence the intention to adopt AI-based technologies. The analysis demonstrated that the influence of market uncertainty on adoption intentions is insignificant. It was found that government regulation and complexity negatively influence adoption intentions. The findings of the study would be valuable for AI-based technology providers, IT managers and top management in organizations, and government bodies, in terms of building effective policies to promote the successful adoption of AI-based technologies.

Blockchain Technology Model Towards Smart Agriculture: A Proposed Model

The objective of this study is to examine the challenges created by blockchain technology to the agriculture stakeholders. Besides that, it is also noteworthy to understand that two important theories underlie the integration towards achieving the objectives of developing the blockchain technology for smart agriculture are the Grounded Theory and will conceptualise the Technology-Organisation-Environment (TOE) Theory. This study employs a qualitative approach because it can extract the complex description of the blockchain technology towards smart agriculture that involves various agriculture sector stakeholders. Semi-structured in-depth interviews will be conducted in six states: Perlis, Kedah, Selangor, Negeri Sembilan, Pahang and Sarawak as part of the research to get a more in-depth understanding of the profiles and better understanding on the challenges created by blockchain technology to the agriculture stakeholders. Drawing on the high value of smart agriculture principles, this study reconciles a comprehensive blockchain technology model and draw connections with the challenges faced by various stakeholders. This study expands knowledge on blockchain technology in supporting smart agriculture by looking into the blockchain technology attributes in terms of traceability, visibility, security and accessibility, as well as the challenges created by blockchain technology to the agriculture stakeholders. This study output will boost the modernisation process in the agriculture sector, managing the demand and supply of national food and agriculture supply. The underlying trend of agricultural research is discovered to be primarily embedded in scientific investigations from technologies’ perspectives. Researching in smart agriculture is crucial but remains scanty due to the challenges facing at the different levels in the supply chain. As such, the novelty fits within this research model are unavailable to the researchers’ best knowledge.

Identifying the equifinal configurations of prompting green supply chain integration and subsequent performance outcome

AbstractAlthough green supply chain integration (GSCI) is essential for enterprises to address environmental challenges, existing literature mainly focuses on the net effect of a single factor that cannot well explain and guide the implementation of GSCI. Based on technology–organization–environment (TOE) framework, we develop a configurational framework and propose that GSCI depends on the interactions between perceived institutional force, green human resource management (GHRM), and big data analytics capability (BDAC). Moreover, we further investigate the impacts of high GSCI generated by different configurations on operational and environmental performance. By integrating fuzzy set qualitative comparative analysis (fsQCA) and propensity score matching, we reveal multiple equifinal configurations sufficient to three dimensions of GSCI and identify them into three types: GHRM oriented, GHRM + BDAC oriented, and perceived institutional force + GHRM + BDAC balance. The results further indicate that high GSCI triggered by multiple configurations has different effects on operational and environmental performance. These findings extend the GSCI research and provide theoretical guidance for managers to develop GSCI.

Analysis of the Adoption of Digital Marketing in MSMEs in the Era of the Covid-19 Pandemic

Micro, Small and Medium Enterprises (MSMEs) are the most numerous forms of business in Indonesia. This creates high competition among business actors. The conditions of Covid-19 pandemic are increasing the business competition with restriction on community activities including restriction towards business activites set by the government. Many business fields such as food, beverage, and creative industries are affected by this circumstance. MSME actors are trying to survive the business in the midst of a pandemic. Digital marketing is a form of marketing effort by MSMEs so that they can still operate their business. The role of digital marketing is not only to market produts, but also as a means of communicating with customers, disseminating information, and providing convenience for transactions. The purpose of this research is to analyze digital marketing adoption by MSMEs in the era of Covid-19 pandemin in Indonesia. The approach applied in this research is the Technology Organization Environment (TOE) model with quantitative research method. The total of 244 MSMEs are the respondents in this research. The results of this study show that the context of technology, organization and environment has a positive effect on digital marketing adoption by MSMEs in the era of the Covid-19 pandemic.

The appropriation of blockchain implementation in the supply chain of SMES based on fuzzy LMAW

This study investigates the adoption of blockchain technology in small and medium-sized enterprises’ (SMEs) supply chains. Blockchain has been deemed a “Game Changer” for its potential benefits but also has several limitations due to its properties and SMEs’ limited resources. Small and medium-sized companies (SMEs) have more problems employing Industry 4.0 Technologies in practice than larger companies. So, the employment of BC in SMEs’ supply chains, as the economy’s backbone, deserves a full investigation which has been addressed in this paper.We use the Technology–Organization–Environment framework to examine both positive and negative factors affecting blockchain adoption in SMEs. A Delphi method was used to refine a list of 42 factors down to the 22 most essential ones. These factors were then prioritized using the Fuzzy Logarithmic Additive Weights Methodology based on expert preferences. The findings indicate that while financial factors play a crucial role in adoption, transparency, and traceability are significant benefits that motivate organizations to adopt blockchain. The organizational dimension also has a substantial impact on decision-making.In this study, we conclude that SMEs must carefully consider their circumstances before adopting blockchain technology, given its infancy state. The barriers to adoption are just as significant as incentives, and SMEs must weigh the financial and organizational factors before making the decision. This study extends the literature by comprehensively looking at all possible factors influencing BC adoption by SMEs. Furthermore, we have highlighted valuable insights for policymakers and SME owners to make the best decision.

Can China’s Digital Economy and Green Economy Achieve Coordinated Development?

The coordinated development of the digital economy and green economy is a key issue that needs to be addressed. Based on the statistical data of 30 provincial-level regions in China from 2014 to 2019, this study empirically analyzed whether China’s digital economy and green economy can achieve coordinated development. In this study, a coupling coordination degree model was used to evaluate the degree of coordinated development of the digital economy and green economy in provincial regions of China. A fuzzy-set qualitative comparative analysis method was adopted to identify the realization path of the coordinated development of the digital economy and green economy. The results show the following: (1) the coordinated development degree of the digital economy and green economy in China shows an upward trend from primary coordination in 2014 to intermediate-level coordination in 2019, with great differences between different regions; (2) there are five paths to achieve coordinated development of the digital economy and green economy, which are divided into two categories (technology–environment dual-drive type, and technology–organization–environment linkage drive type); (3) technological innovation capability and government financial support can substitute for one another under certain conditions to achieve the coordinated development of the digital economy and green economy. These conclusions provide a theoretical basis for countries to formulate policies to promote the coordinated development of their digital economy and green economy.

Innovation Capabilities as a Mediator between Business Analytics and Firm Performance

Although business analytics (BA) play an important role in improving firm performance, various firms struggle to deliver their full benefits. Many researchers have investigated the capabilities required to achieve better value through BA, but none have addressed the impact of innovation capabilities as a contextual variable mediating the effects on firm performance. By adopting the Technology-Organization-Environment (TOE) framework, this study suggests a model to evaluate the impact of BA capabilities on firm performance and addresses the mediating role of innovation capabilities. A quantitative approach was adopted for data collection and analysis. Based on 386 surveys of BA experts at Saudi Arabian firms and the use of PLS-SEM to test and validate the model. The results show that organizational factors have a highly significant impact on firm performance. While IT infrastructure and information quality as technological factors showed no significant and positive effect. Furthermore, the findings revealed that innovation capabilities positively mediate the link between IT infrastructure and information quality and firm performance as it affects directly and indirectly firm performance. The findings of this study contribute to the literature by addressing the research gap in BA in the Saudi Arabia context. Moreover, the study result stressing about the role of innovation capabilities on the BA capabilities and the importance of considering the interaction between TOE factors. However, research was carried out within one developing country (Saudi Arabia), which might restrict the findings’ generalizability of the study, and the results must be generalized with care to avoid issues such as structural and cultural variances between developed and developing countries.

Analysis of IoT adoption for vegetable crop cultivation: Multiple case studies

This study aims to fill a gap in the literature regarding the interrelationship between agricultural modernization and the internet of things (IoT), particularly in vegetable crop cultivation. Therefore, it focuses on understanding the barriers to and enablers of IoT adoption in planting and harvesting vegetables. We built a theoretical framework that incorporates the constructs of individual and organizational technology adoption models, linking behavioral, technological, organizational, and environmental factors. The framework is supported by the technology-organization-environment (TOE) and unified theory of acceptance and use of technology (UTAUT) models. We conducted in-depth interviews with 15 producers, three agricultural sector experts, and four suppliers. The results showed that only established producers implemented technology, indicating that organizational factors are decisive for the adoption of the IoT. Thus, the producer's size, knowledge, management level, and investment power affect IoT adoption. The theoretical model needs to be assessed according to producers' size, thereby revealing that organizational factors directly influence producers' behavioral issues.

Insights into customers' psychological mechanism in facial recognition payment in offline contactless services: integrating belief–attitude–intention and TOE–I frameworks

PurposeFacial recognition payment is an emerging mobile payment method that uses human biometrics for personal identification. The purpose of this study is to examine how users' salient beliefs regarding the technology–organization–environment–individual (TOE–I) dimensions affect their attitudes and how attitudes subsequently influence the intention to use facial recognition payment in offline contactless services.Design/methodology/approachThis study comprehensively investigates customers' decision-making psychological mechanism of using facial recognition payment by integrating the belief–attitude–intention (B–A–I) model and the extended TOE–I framework. Data from 420 valid samples were collected through an online survey and analyzed using partial least squares structural equation modeling.FindingsResearch results indicate that convenience and perceived herd exert positive effects on trust and satisfaction. Meanwhile, familiarity has a significantly positive effect only on trust but not on satisfaction. In contrast, perceived privacy risk exhibits a negative effect on both trust and satisfaction. Trust and satisfaction positively influence the intention to use facial recognition payment. Unexpectedly, self-awareness negatively moderates the effect of satisfaction on intention to use, but its effect on the relationship between trust and intention to use is non-significant.Originality/valueTo the best of the authors’ knowledge, this study is one of the early studies that explicate customers' psychological mechanism in facial recognition payment in offline contactless services through an understanding of the B–A–I causal linkages with the identification of users' perceptions from a comprehensive context-specific perspective. This study enriches the literature on facial recognition payment and explores the moderating role of self-awareness in the relationship between users' attitudes and intention to use, thereby revealing a complex psychological process in the usage of offline facial recognition payment systems.

Internet of Things Adoption in the Manufacturing Sector: A Conceptual Model from a Multi-Theoretical Perspective

The manufacturing sector (MS) is considered one of the most important national economic sectors; therefore, global manufacturers strive to apply cutting-edge technologies to gain competitive advantages. The Internet of Things (IoT) has an inherent potential to enhance MS economic growth and maintain its dominance in global markets by using a vast network of smart sensors; nevertheless, IoT technology adoption in the MS remains in the early phase. This research aims to define the antecedents that affect IoT adoption in the MS and propose a conceptual model to explain the adoption intention. Based on an extensive literature review, the proposed model was constructed by three main antecedents: perceived value, perceived benefits, and perceived challenges, and 11 related variables. The model development used a multi-theoretical perspective by integrating three theories: the value-based adoption model, the diffusion of innovation theory, and the technology–organization–environment framework. This study provides decision-makers with valuable insight that promotes IoT adoption in MS and enriches the literature with a new perspective that encourages more studies on IoT adoption in organizations.

Reaching for the “Cloud”

Cloud computing adoption and utilization is gaining prominence in most developing countries. Its adoption is influenced by several factors, which can constitute a limitation rather than an advantage for firms. This research, therefore, explored the issues surrounding the adoption of cloud computing by small and medium-sized enterprises (SMEs) in a developing economy. An SME operating in Ghana for over five years was purposively selected as the case for the study. Technology-organization-environment (TOE) framework served as a guiding lens. Interviews were held with selected staff of the case firm. Data were analyzed using the Miles and Huberman's transcendental realism technique. It was discovered that the motivation for cloud computing adoption is the possibility of getting a state-of-the-art IT infrastructure at the lowest cost possible. The study presents the factors that influenced cloud computing adoption in the SME. The study contributes to improving the present understanding of cloud computing as an SME's strategic tool for operating within a developing economy.