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The advent of robotics and automation technologies was augmenting firm initiatives to attain competitive advantage. From a resource-based view perspective, human-led capabilities were important to operate with technology resource base of an organisation. This was evident for both manufacturing as well as services firms. However, employees as an individual confronted technology anxiety (TA) when they were working with new technologies like robotics and automation technologies. Thus, the purpose of this paper was to examine the factors causing TA.

Given the novelty of this research study context a qualitative exploratory method was designed. For this research study, the data collected was through in-depth interviews conducted through open-ended semi-structured questionnaire. The data was collected from 62 frontline employees who were working with robotics and automation-based technologies in manufacturing firms. The authors applied thematic content analysis on collected data for analysis.

Technology anxieties ranged from fear of complete inability to learn new technologies, failure to learn new technologies properly, incapability to implement the learned skills and job loss to younger technology savvy employees. Finally, there was anxiety over job loss as automation and robotic technologies over the years was expected to erode the employment of human workforce altogether.

The author undertook the research study based upon the TA perspective advocated by Meuter et al. (2003) and Yang and Forney (2013). Furthermore, this research study in the context of robotics and automation-based technologies in the manufacturing sector applied the mental accounting theory (Thaler, 1999) and technology self-efficacy perspective (Huffman et al., 2013).

Managers involved in the implementation of robotics and automation-based technologies were required to address TA of employees. Fear of job loss had to be addressed specially in a country like India. Anxiety regarding the ability to learn to work with robotics and automation technologies also was needed to be addressed by managers through adequate training and time for preparation. The benefits of robotics and automation-based technologies for employees as well as organisations have to be ascertained through open communication between the management and the frontline employees.

To the best of the authors’ knowledge, this was one of the first empirical research studies which deliberated regarding TA in the context of frontline workers working with robotics and automation-based technologies in the manufacturing sector. This research study was based upon a combination of varied perspectives ranging from micro foundations theory, TA, mental accounting theory and technology self-efficacy perspective.

Nuclear power is a stable and reliable energy source that can improve energy structure while reducing carbon emissions, which is of great significance for environmental protection and combating climate change. As a unique industry, it is facing rare development opportunities in China and has broad market prospects. However, the characteristics of technical difficulty, loose organizational structure and uneven regional distribution limit the expansion of the nuclear power industry. This paper aims to a better understanding of the accumulation process for innovation capability from the perspective of network evolution and provides policy guidance for the market development of the nuclear power industry (NPI).

Methodologically, social network analysis is used to explore the co-evolution of multidimensional collaboration networks. First, the development and policy evolution of the NPI is introduced to divide the evolution periods. Then, the authors identify and analyze the core organizations, technologies and regions that promote nuclear power patent collaboration. Furthermore, three levels of collaboration networks based on organizations, technologies and regions are constructed to analyze the coevolution of patent networks in China’s NPI.

The results show that nuclear power enterprises always play the foremost role in the organizational collaboration network (OCN), and the dominance of foreign enterprises is replaced by Chinese state-owned enterprises in the third period. The technology hotspot has shifted from nuclear power plant construction to the control system. The regional collaboration network was initially formed in the coastal areas and gradually moved inland, with Guangdong and Beijing becoming the two cores of the network. The scale of three collaboration networks is still expanding but the speed has slowed down.

In response to the pain points of the NPI, this research focuses on multidimensional collaborative innovation, investigates the dynamic evolution process of collaborative innovation networks in China’s NPI and links policy evolution with network evolution creatively. The ultimate result not only helps nuclear power enterprises integrate innovative resources in complex environments but also promotes industrial upgrading and market development.

With the increasing number of mobile applications, efficiently recommending mobile applications to users has become a challenging problem. Although existing mobile application recommendation approaches based on user attributes and behaviors have achieved notable effectiveness, they overlook the diffusion patterns and interdependencies of topic-specific mobile applications among user groups. mobile applications among user groups. This paper aims to capture the diffusion patterns and interdependencies of mobile applications among user groups. To achieve this, a topic-aware neural network-based mobile application recommendation method, referred to as TN-MR, is proposed.

In this method, first, the user representations are enhanced by introducing a topic-aware attention layer, which captures both the topic context and the diffusion history context. Second, it exploits a time-decay mechanism to simulate changes in user interest. Multitopic user representations are aggregated by the time decay module to output the user representations of cascading representations under multiple topics. Finally, user scores that are likely to download the mobile application are predicted and ranked.

Experimental comparisons and analyses were conducted on the actual 360App data set, and the results demonstrate that the effectiveness of mobile application recommendations can be significantly improved by using TN-MR.

In this paper, the authors propose a mobile application recommendation method based on topic-aware attention networks. By capturing the diffusion patterns and dependencies of mobile applications, it effectively assists users in selecting their applications of interest from thousands of options, significantly improving the accuracy of mobile application recommendations.

Customer value perception of Internet of Things (IoT)-based services has not been studied in the context of a company’s readiness to adopt IoT technology. The purpose of this paper is to address this gap by indicating a research framing that combines insights from the IoT business model literature and customer perception of the value of such models and their drivers.

The interplay between a company’s IoT readiness and its perception of the value of IoT services is tested using a sample of 90 Eastern European business customers in a competitive business field. The conceptual framework described also examines relationships among constructs that refer to relationship quality. This study evaluates its quantitative sample using partial least squares path modeling.

Customers’ perceived value of IoT business models strongly relates to their digitalization capabilities and their own company’s innovativeness. When referring to disruptive technical offerings, existing trustful and satisfactory relationships cannot enhance the customer’s value perception.

The sample of Eastern European buyers is not representative of the majority of manufacturing companies. A randomized sample using other sources such as large industry databases could be useful. In addition, a replication of the study in other countries would allow for a cross-border validation of this study’s results.

This study suggests a detailed process that is based on a careful preselection of test customers working for innovative companies. A marketing communication approach must state clearly the benefits the buyers get in return for their sacrifice of sharing data.

Technology readiness refers to the user’s propensity to embrace and use new technologies. The results indicate that IoT readiness influences the successful launch of IoT-related business models. For managers, this study proposes a process to implement IoT-related business models.

The purpose of this study is to examine how Industry 4.0 (I4.0) implementation might improve marketing performance (MP). Early adopters now have the chance to capitalize on the advantages of this successful implementation owing to the transition to I4.0. To improve MP, businesses must be able to identify and manage their effective implementation of I4.0 technologies, which are essential to improve industrial performance.

A survey was created and sent to 311 samples of manufacturing companies. To investigate the hypothesis created in this context, the study includes a survey-based analysis. To present the study’s findings, partial least squares-structural equation modeling has been used.

According to the findings, it can be concluded that an efficient implementation of Industry 4.0 (EII) can improve MP by positively impacting consumer loyalty and increasing customer loyalty (CL) positively enhancing by product customization (PC). The study’s key results, however, are how both PC and CL affect MP.

The intensive production technologies that are at the center of I4.0 will be better understood by professionals thanks to this study. The Internet of Things, artificial intelligence, additive manufacturing, sophisticated robots and many more are examples of these technologies. I4.0’s application strengthens efficiency and high-quality production. The I4.0 concept is gaining popularity in both developed and emerging countries due to its higher performance. Additionally, business people are actively working to implement I4.0 and make it a big success.

The study identifies the successful adoption of I4.0 that has a substantial impact on businesses’ MP. However, there is a lack of noteworthy studies that can concentrate on the marketing reach with I4.0 deployment. As a result, the goal of the current research is to comprehend how I4.0 will affect MP.

The internationalization of business has grown the production value chains and created performance challenges for industrial production. Industry 4.0, the digital transformation of industrial processes, promises to deliver performance improvements through smart functionalities. This study investigates how digital transformation translates to performance gain by adopting a systems perspective to drive smartness.

This study uses qualitative research to collect data on the lived experiences of digital transformation practitioners for theory development. It uses semi-structured interviews with industry experts and applies the Gioia methodology for analysis.

The study determined that enterprise smartness is an organizational capability developed by digital transformation, it is a function of integration and the enabler of organizational performance gains in the Industry 4.0 context. The study determined that performance gains are experienced in productivity, sustainability, safety and customer experience, which represents performance metrics for Industry 4.0.

This study contributes a model that inserts smartness in the linkage between digital transformation and organizational outcomes to the digital transformation and production management literature.

The study indicates that digital transformation programs should focus on developing smartness rather than technology implementations, which must be considered an enabling activity.

Existing studies recognized the positive impact of technology on performance in industrial production. The study addresses a missing link in the Industry 4.0 value creation process. It adopts a systems perspective to establish the role of smartness in translating technology use to performance outcomes. Smart capabilities have been the critical missing link in the literature on harnessing digital transformation in organizations. The study advances theory development by contributing an Industry 4.0 value model that establishes a link between digital technologies, smartness and organizational performance.

Existing studies have paid less attention to the impact of knowledge accumulation on digital transformation and its boundary conditions. Hence, this study aims to investigate the effects of ambidextrous knowledge accumulation on manufacturing digital transformation under the moderation of dynamic capability.

This study divides knowledge accumulation into exploratory and exploitative knowledge accumulation and divides dynamic capability into alliance management capability and new product development capability. To clarify the relationship among ambidextrous knowledge accumulation, dynamic capability and manufacturing digital transformation, the authors collect data from 421 Chinese listed manufacturing enterprises from 2016 to 2020 and perform analysis by multiple hierarchical regression method, heterogeneity test and robustness analysis.

The empirical results show that both exploratory and exploitative knowledge accumulation can significantly promote manufacturing digital transformation. Keeping ambidextrous knowledge accumulation in parallel is more conducive than keeping single-dimensional knowledge accumulation. Besides, dynamic capability positively moderates the relationship between ambidextrous knowledge accumulation and manufacturing digital transformation. Moreover, the heterogeneity test shows that the impact of ambidextrous knowledge accumulation and dynamic capabilities on manufacturing digital transformation varies widely across different industry segments or different regions.

First, this paper shifts attention to the role of ambidextrous knowledge accumulation in manufacturing digital transformation and expands the connotation and extension of knowledge accumulation. Second, this study reveals that dynamic capability is a vital driver of digital transformation, which corroborates the previous findings of dynamic capability as an important driver and contributes to enriching the knowledge management literature. Third, this paper provides a comprehensive micro measurement of ambidextrous knowledge accumulation and digital transformation based on the development characteristics of the digital economy era, which provides a theoretical basis for subsequent research.

This study aims to investigate the contribution of blockchain technology to supply chain risk management and its impact on performance among Indian manufacturing companies.

Drawing on a resource-based view, dynamic capability and system of systems theory, this study examines the direct relationships between blockchain, supply chain risk management and supply chain performance. The authors validate the mediating effects of three supply chain risk management components, namely supply risk management, demand risk management and cyber security management, on financial transaction reliability and information reliability. Data were collected from 204 Indian manufacturing companies that have adopted blockchain technology.

The results demonstrate that companies adopting blockchain technology have experienced positive outcomes in managing supply chain-related risks, financial transaction reliability and information reliability. These findings provide valuable guidance to managers, highlighting blockchain as a competitive advantage for supply chain management.

To the best of the authors’ knowledge, no previous research on blockchain-based risk management capabilities has been conducted.

This research deals with the critical factors of quality and their significance to perceived security as an effort to build a formidable loyalty of customers in a technology driven service environment. The primary purpose of this study is to investigate the key contributing elements of functional and service quality on perceived security and to further analyze its impact on customer satisfaction and loyalty.

A hypothesized structure model is proposed and justified using the data collected in the manufacturing and telecommunication service sectors in South Korea through survey with total 647 respondents. To clarify the reliability of model and validity of the proposed hypothesis, AMOS 24.0 software was utilized. Furthermore, two moderating variables were adopted for the depth understanding.

This study reveals that service quality dominantly influences the level of perceived security due to its characteristics that are mostly formed on the stage of customer-contact activity. This study further provides a strategic methodology for manufacturing and telecommunication firms to foster sustainable growth by focusing on perceived security during the service delivery process.

This finding is particularly important as Ontact technology becomes increasingly critical during the COVID-19 pandemic. It is worthwhile noting that the research outcome of this study may, in turn, trigger the trust issue that need to be combined with quality in the era of Industry 4.0.

Using social network theory (SNT), this study empirically examines the impact of digital supply chain announcements disclosing corporate social responsibility (CSR) information on stock market value.

Based on 172 digital supply chain announcements disclosing CSR information from Chinese A-share listed companies, this study uses event study method to test the hypotheses.

First, digital supply chain announcements disclosing CSR information generate positive and significant market reactions, which is timely. Second, strategic CSR and value-based CSR disclosed in digital supply chain announcements have a more positive impact on stock market, however there is no significant difference when the CSR orientation is either towards internal or external stakeholders. Third, in terms of digital supply chain network characteristics, announcements reflecting higher relationship embeddedness and higher digital breadth and depth lead to more positive increases of stock value.

First, the authors consider the value of CSR information in digital supply chain announcements, using an event study approach to fill the gap in the related area. This study is the first examination of the joint impact of digital supply chain and CSR on market reactions. Second, compared to the previous studies on the single dimension of digital supply chain technology application, the authors innovatively consider supply chain network relationship and network structure based on social network theory and integrate several factors that may affect the market reaction. This study improves the understanding of the mechanism between digital supply chain announcements disclosing CSR information and stock market, and informs future research.