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This paper aims at investigating the role of institutional entrepreneurship and corporate entrepreneurship to cope with firm’ impasses by adoption of the new technology ahead of other firms. Also, this paper elucidates the importance of own specific institutional and corporate entrepreneurship created from firm’s norm.

The utilized research frame is as follows: first, perspective of studies on institutional and corporate entrepreneurship are performed using prior literature and preliminary references; second, analytical research frame was proposed; finally, phase-based cases are conducted so as to identify research objective.

Kumho Tire was the first tire manufacturer in the world to exploit the utilization of radio-frequency identification for passenger carâ’s tire. Kumho Tire takes great satisfaction in lots of failures to develop the cutting edge technology using advanced information and communication technology cultivated by heterogeneous institution and corporate entrepreneurship.

The firm concentrated its resources into building the organization’s communication process and enhancing the quality of its human resources from the early stages of their birth so as to create distinguishable corporate entrepreneurship.

The purpose of this paper is to analyze the trends of global automobile industry toward energy saving and smart application. The automobile industry has its own special supply, safety and reliability system. It combined with the legislations that progressive safety driving leads to increase automobile electronic (AE) facilities and enlarges the proportion of the electronic control for vehicles. Based on matured communication and semiconductor industries in Taiwan, the government assists these hi-tech industries in entering the AE domain by clustering relevant enterprises with assembly supply chains. Flagship IC packaging and LCD panels enterprises are located in the Kaohsiung Industrial Park which possesses advantages for the clustering of AE industry.

In this paper, a systematic investigation on establishing AE industry cluster in Kaohsiung Industry Park (KIP) is presented. First, 42 electrical and electronics enterprises are site visited and interviewed for operation and management preferential demands. Second, problems encountered in enterprises’ operation are identified through expert weight method. Third, the main factors involved in the operational management are then analyzed based on five flagship enterprises in KIP. The integration of industrial–university–government resources and assistance is demonstrated. Finally, the establishment of an innovative talents cultivation model is illustrated.

The developed systematic talent program is proposed to resolve the urgent demands in recruiting talents, operational costs and new products development.

This paper satisfies needs of research enterprise management. The establishment of an innovative talents cultivation model is illustrated.

This paper investigated the organizational adoption of big data analytics (BDA) in the context of supply chain planning (SCP) to conceptualize how resources are orchestrated for organizational BDA adoption and to elucidate how resources and capabilities intervene with the resource management process during BDA adoption.

This research elaborated on the resource orchestration theory and technology innovation adoption literature to shed light on BDA adoption with multiple case studies.

A framework for the resource orchestration process in BDA adoption is presented. The authors associated the development and deployment of relevant individual, technological and organizational resources and capabilities with the phases of organizational BDA adoption and implementation. The authors highlighted that organizational BDA adoption can be initiated before consolidating the full resource portfolio. Resource acquisition, capability development and internalization of competences can take place alongside BDA adoption through structured processes and governance mechanisms.

A relevant discussion identifying the capability gap and provides insight into potential paths of organizational BDA adoption is presented.

The authors call for attention from policymakers and academics to reflect on the changes in the expected capabilities of supply chain planners to facilitate industry-wide BDA transition.

This study opens the black box of organizational BDA adoption by emphasizing and scrutinizing the role of resource management actions.

The purpose of this paper is to present a conceptual model that defines the essential components shaping the new Digital Supply Chains (DSCs) through the implementation and acceleration of Industry 4.0.

The scope of the present work exposes a conceptual approach and review of the key literature from 1989 to 2019, concerning the evolution and transformation of the actors and constructs in logistics and Supply Chain Management (SCM) by means of examining different conceptual models and a state-of-the-art review of Industry 4.0’s concepts and elements, with a focus on digitization in supply chain (SC) processes. A detailed study of the constructs and components of SCM, as defined by their authors, resulted in the development of a referential and systematic model that fuses the inherent concepts and roles of SCM, with the new technological trends directed toward digitization, automation, and the increasing use of information and communication technologies across logistics global value chains.

Having achieved an exploration of the different conceptual frameworks, there is no compelling evidence of the existence of a conceptual SCM that incorporates the basic theoretical constructs and the new roles and elements of Industry 4.0. Therefore, the main components of Industry 4.0 and their impact on DSC Management are described, driving the proposal for a new conceptual model which addresses and accelerates a vision of the future of the interconnectivity between different DSCs, grouped in clusters in order to add value, through new forms of cooperation and digital integration.

This research explores the gap in the current SCM models leading into Industry 4.0. The proposed model provides a novel and comprehensive overview of the new concepts and components driving the nascent and current DSCs. This conceptual framework will further aid researchers in the exploration of knowledge regarding the variables and components presented, as well as the verification of the newly revealed roles and constructs to understand the new forms of cooperation and implementation of Industry 4.0 in digitalized SCs.

The coronavirus (COVID-19) has had a tremendous impact on companies worldwide. However, researchers have no clear idea of the key issues requiring their attention. This paper aims to close this gap by analysing all business-related posts on a coronavirus subreddit (“r/coronavirus”) and identifying the main research streams that are guiding the research agenda for a post-coronavirus world.

We use data from reddit, particularly the subreddit “r/coronavirus” to identify posts that reveal the impact of coronavirus on business. Our dataset has more than 200,000 posts. We used an artificial intelligence–based algorithm to scrape the data with business-related search terms, clean it and analyse the discussion topics.

We show the key topics that address the impact of coronavirus on business, combining them into four themes: essential service provision, bricolage service innovation, responsible shopping practices and market shaping amid crisis. We discuss these themes and use them to develop a service research agenda. The results are reported against the backdrop of service research priorities.

The study identifies four key themes that have emerged from the impact of coronavirus on business and that require scholarly attention. Our findings can guide service research with unique insights provided immediately after the coronavirus outbreak to conduct research that matters to business and helps people in vulnerable positions in a post-coronavirus world.

Advanced driving assistance system (ADAS) has been applied in commercial vehicles. This paper aims to evaluate the influence factors of commercial vehicle drivers’ acceptance on ADAS and explore the characteristics of each key factors. Two most widely used functions, forward collision warning (FCW) and lane departure warning (LDW), were considered in this paper.

A random forests algorithm was applied to evaluate the influence factors of commercial drivers’ acceptance. ADAS data of 24 commercial vehicles were recorded from 1 November to 21 December 2018, in Jiangsu province. Respond or not was set as dependent variables, while six influence factors were considered.

The acceptance rate for FCW and LDW systems was 69.52% and 38.76%, respectively. The accuracy of random forests model for FCW and LDW systems is 0.816 and 0.820, respectively. For FCW system, vehicle speed, duration time and warning hour are three key factors. Drivers prefer to respond in a short duration during daytime and low vehicle speed. While for LDW system, duration time, vehicle speed and driver age are three key factors. Older drivers have higher respond probability under higher vehicle speed, and the respond time is longer than FCW system.

Few research studies have focused on the attitudes of commercial vehicle drivers, though commercial vehicle accidents were proved to be more severe than passenger vehicles. The results of this study can help researchers to better understand the behavior of commercial vehicle drivers and make corresponding recommendations for ADAS of commercial vehicles.

The research approach is based on the concept that a failure event is rarely random and is often generated by a chain of previous events connected by a sort of domino effect. Thus, the purpose of this study is the optimal selection of the components to predictively maintain on the basis of their failure probability, under budget and time constraints.

Assets maintenance is a major challenge for any process industry. Thanks to the development of Big Data Analytics techniques and tools, data produced by such systems can be analyzed in order to predict their behavior. Considering the asset as a social system composed of several interacting components, in this work, a framework is developed to identify the relationships between component failures and to avoid them through the predictive replacement of critical ones: such relationships are identified through the Association Rule Mining (ARM), while their interaction is studied through the Social Network Analysis (SNA).

A case example of a process industry is presented to explain and test the proposed model and to discuss its applicability. The proposed framework provides an approach to expand upon previous work in the areas of prediction of fault events and monitoring strategy of critical components.

The novel combined adoption of ARM and SNA is proposed to identify the hidden interaction among events and to define the nature of such interactions and communities of nodes in order to analyze local and global paths and define the most influential entities.

Recently, disruptive technologies (DTs) have proposed several innovative applications in managing logistics and promise to transform the entire logistics sector drastically. Often, this transformation is not successful due to the existence of adoption barriers to DTs. This study aims to identify the significant barriers that impede the successful adoption of DTs in the logistics sector and examine the interrelationships amongst them.

Initially, 12 critical barriers were identified through an extensive literature review on disruptive logistics management, and the barriers were screened to ten relevant barriers with the help of Fuzzy Delphi Method (FDM). Further, an Interpretive Structural Modelling (ISM) approach was built with the inputs from logistics experts working in the various departments of warehouses, inventory control, transportation, freight management and customer service management. ISM approach was then used to generate and examine the interrelationships amongst the critical barriers. Matrics d’Impacts Croises-Multiplication Applique a Classement (MICMAC) analysed the barriers based on the barriers' driving and dependence power.

Results from the ISM-based technique reveal that the lack of top management support (B6) was a critical barrier that can influence the adoption of DTs. Other significant barriers, such as legal and regulatory frameworks (B1), infrastructure (B3) and resistance to change (B2), were identified as the driving barriers, and industries need to pay more attention to them for the successful adoption of DTs in logistics. The MICMAC analysis shows that the legal and regulatory framework and lack of top management support have the highest driving powers. In contrast, lack of trust, reliability and privacy/security emerge as barriers with high dependence powers.

The authors' study has several implications in the light of DT substitution. First, this study successfully analyses the seven DTs using Adner and Kapoor's framework (2016a, b) and the Theory of Disruptive Innovation (Christensen, 1997; Christensen et al., 2011) based on the two parameters as follows: emergence challenge of new technology and extension opportunity of old technology. Second, this study categorises these seven DTs into four quadrants from the framework. Third, this study proposes the recommended paths that DTs might want to follow to be adopted quickly.

The authors' study has several managerial implications in light of the adoption of DTs. First, the authors' study identified no autonomous barriers to adopting DTs. Second, other barriers belonging to any lower level of the ISM model can influence the dependent barriers. Third, the linkage barriers are unstable, and any preventive action involving linkage barriers would subsequently affect linkage barriers and other barriers. Fourth, the independent barriers have high influencing powers over other barriers.

The contributions of this study are four-fold. First, the study identifies the different DTs in the logistics sector. Second, the study applies the theory of disruptive innovations and the ecosystems framework to rationalise the choice of these seven DTs. Third, the study identifies and critically assesses the barriers to the successful adoption of these DTs through a strategic evaluation procedure with the help of a framework built with inputs from logistics experts. Fourth, the study recognises DTs adoption barriers in logistics management and provides a foundation for future research to eliminate those barriers.