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Innovation is the fundamental driving force for the long-term sustainable development of an economy. After four decades of rapid economic growth, China is facing crises related to a demographic structure of “aging before getting rich,” industrial overcapacity of low-end products and environmental and resources constraints. This paper aims to discuss these issues.

Based on logical analysis and recapitulation of previous empirical research, this study presents the conclusion.

Scientific and technological innovation, as strategic support to improve social productivity and overall national strength, must be placed at the center of the country’s overall development.

The development model that preys upon cheap resources for extensive growth is unsustainable. Thus, the country needs an urgent strategic switch to drive its economic growth through research and development innovation and original technological advancement.

This paper aims to introduce the history and major achievement of the Chinese private enterprise survey (CPES), which is one of the most enduring large-scale nationwide sample surveys in China, providing important micro firm-level data for understanding and studying the development of Chinese enterprises and entrepreneurs over the past 26 years.

The main body of this paper is based on a bibliometric analysis of all literature using CPES until 2017.

This paper discusses problems that users may encounter during data mining. By doing so, it can assist other researchers to get a better understanding of what has been done (e.g. journals, topics, scholars and institutions) and do their research in a more targeted way.

As members of the survey project team, the authors also take a prospect of the future data design and use, as well as offer some suggestions about how to use the CPES data to improve high-quality development and business environment evaluation in China.

This paper is the first to provide an overall picture of academic papers in China and abroad that have used the CPES data.

Notwithstanding its significance as a form of strategic human capital investment, employee training has not yielded consistent conclusions among scholars regarding its impact on organizational performance. Some studies deem it effective, while others regard it as ineffective. We contend that distinct types of training impact various facets of firm performance.

In this study, we categorize employee training as either exploitative or explorative. Specifically, we examine their impact on two aspects of organizational performance: short-term performance and long-term competence, using a quasi-experimental setting and a difference-in-differences (DID) method.

We find that exploitative training is more effective in improving firms’ short-term performance (e.g. firms’ sales revenue), while explorative training is more effective in enhancing firms’ long-term competence (e.g. firms’ innovation output).

The findings of this study illuminate concrete benefits of training for practitioners, suggesting that firms can strategically select employee training category to maximize returns on their investment in strategic human capital based on their strategic orientations.

Blockchain technology is booming in many industries. Its application in supply chain management is also gradually increasing. Supply chain management (SCM) has long been committed to reducing costs and increasing efficiency and is trying to optimise resources and reduce the sector's fragmentation. Trust has always been an important factor in managing supply chain relationships, and it also affects the efficiency of supply chain operations. To this end, this study aims to examine how trust is affected by the introduction of blockchain technology in construction supply chain management.

This study is based on semi-structured interviews and publicly available information from experts in blockchain and construction supply chain management. Through content analysis, the data are analysed thematically to explore how various types of trust, such as system-based, cognition-based and relation-based, are affected by blockchain technology.

Blockchain technology provides solutions for data tracking, contracting and transferring resources in supply chain management. These applications help enhance the various sources of trust in SCM and provide supply chain partners with protection mechanisms to avoid the risks and costs of opportunistic behaviour in collaboration, shifting trust from relational to system-based and cognition-based.

This study focuses only on inter-organisational rather than interpersonal trust and empirical data from experts whose knowledge and cognition could be subjective.

Leveraging the potential of digitalisation to manage trust requires that leaders and managers actively try to improve contractual arrangements, information sharing and being open to new innovative technologies like blockchain.

From a relational view of supply chain management, the extent to which blockchain technology can develop and spread depends on the readiness of the social capital to accept decentralised governance structures.

This study builds upon an original data set and discusses features and applications of blockchain technology, explores the sources and dimensions of trust in supply chain management and explains the impact of blockchain technology on trust.

The last decade has seen a significant increase in self-initiated expatriation research across various cohorts; however, limited research exists on the self-initiated expatriation of medical doctors despite their high mobility rates. The purpose of this paper is to investigate the determinants of cross-cultural adjustment among self-initiated medical doctors working and living in a host culture.

A questionnaire was distributed to self-initiated expatriate (SIE) doctors working in Irish hospitals. In total, 193 valid responses were collected. Three linear regression analyses were conducted to explore factors influencing cross-cultural adjustment among SIE medical doctors, along with qualitative insight into their adjustment to working and living in Ireland.

This study found that age, marital status, cultural novelty, previous international work experience, length of time working in the host culture did not influence the cross-cultural adjustment of SIE doctors. However, gender, language ability and perceived fair treatment were found to influence their cross-cultural adjustment in the study. Specifically, female SIE doctors reported higher levels of general adjustment to that of SIE male doctors. SIE doctors' language ability was found to influence their work adjustment, and those who perceived unfair treatment in the host culture reported lower levels of general adjustment.

This paper contributes to the limited knowledge and understanding surrounding the self-initiated expatriation of medical doctors and their cross-cultural adjustment to the host hospital and host culture.

Team leaders play a vital role in achieving superior team performance. However, their role in implementing the organizational customer orientation strategy is not well understood. Drawing on social exchange theory, this study investigates how team leader customer orientation affects team customer orientation climate and team performance (i.e. customer satisfaction) as well as the moderating role of transformational leadership in such effect.

This study builds on survey data collected from matched team leaders, employees and customers nested in 81 service teams and employs hierarchical multiple regression analysis to test the hypotheses.

The findings indicate that team leader customer orientation increases team customer orientation climate, which leads to a higher level of customer satisfaction. Leaders' transformational leadership moderates the link between a leader customer orientation and team customer orientation climate in an unexpected way. When a team leader is transformational, the team customer orientation climate is enhanced, regardless of the level of team leader customer orientation. When a team leader's transformational leadership is low, the higher leader customer orientation is and the higher team customer orientation climate is.

This study contributes to the customer orientation, transformational leadership and service literature by unraveling team leaders' roles in boosting team customer orientation climate and team effectiveness.

Distribution network protection is a complicated problem and mal-operation of the protective relays due to false settings make the operation of the network unreliable. Besides, obtaining proper settings could be very complicated. This paper aims to discuss an innovative evolutionary Lightning Flash Algorithm (LFA) which is developed for solving the relay coordination problems in distribution networks. The proposed method is inspired from the movements of cloud to ground lightning strikes in a thunderstorm phenomenon. LFA is applied on three case study systems including ring, interconnected and radial distribution networks. The power flow analysis is performed in Digsilent Power Factory software; then the collected data are sent to MATLAB software for optimization process. The proposed algorithm provides optimum time multiplier setting and plug setting of all digital overcurrent relays in each system. The results are compared with other methods such as particle swarm optimization and genetic algorithm. The result comparisons demonstrate that the proposed LFA can successfully obtain proper relay settings in distribution networks with faster speed of convergence and lower total operation time of relays. Also, it shows the superiority and effectiveness of this method against other algorithms.

A novel LFA is designed based on the movements of cloud to ground lightning strikes in a thunderstorm. This method is used to optimally adjust the time multiplier setting and plug setting of the relays in distribution system to provide a proper coordination scheme.

The proposed algorithm was tested on three case study systems, and the results were compared with other methods. The results confirmed that the proposed method could optimally adjust the relay settings in the electric distribution system to provide a proper protection scheme.

The practical implications can be conducted on distribution networks. The studies provided in this paper approve the practical application of the proposed method in providing proper relay protection in real power system.

This paper proposes a new evolutionary method derived from the movements of cloud to ground lightning strikes in thunderstorm. The proposed method can be used as an optimization toolbox to solve complex optimization problems in practical engineering systems.

While the proliferation of chatbots allows companies to connect with their customers in a cost- and time-efficient manner, it is not deniable that they quite often fail expectations and may even pose negative impacts on user experience. The purpose of the study is to empirically explore the negative user experience with chatbots and understand how users respond to service failure caused by chatbots.

This study adopts a qualitative research method and conducts thematic analysis of 23 interview transcripts.

It identifies common areas where chatbots fail user expectations and cause service failure. These include their inability to comprehend and provide information, over-enquiry of personal or sensitive information, fake humanity, poor integration with human agents, and their inability to solve complicated user queries. Negative emotions such as anger, frustration, betrayal and passive defeat were experienced by participants when they interacted with chatbots. We also reveal four coping strategies users employ following a chatbots-induced failure: expressive support seeking, active coping, acceptance and withdrawal.

Our study extends our current understanding of human-chatbot interactions and provides significant managerial implications. It highlights the importance for organizations to re-consider the role of their chatbots in user interactions and balance the use of human and chatbots in the service context, particularly in customer service interactions that involve resolving complex issues or handling non-routinized tasks.

This study aims to explore how online reviews and users’ social network centrality interact to influence idea popularity in open innovation communities (OICs).

This study used Python to obtain data from the LEGO Innovation Community. In total, 285,849 reviews across 4,475 user designs between March 2019 and March 2021 were extracted to test this study’s hypotheses.

The ordinary least square regression analysis results show that review volume, review valence, review variance and review length all positively influence idea popularity. In addition, users’ in-degree centrality positively interacts with review valence, review variance and review length to influence idea popularity, while their out-degree centrality negatively interacts with such effects.

Drawing on the interactive marketing perspective, this study employs a large sample from the LEGO community and examines user design and idea popularity from a community member’s point of view. Moreover, this study is the first to confirm the role of online reviews and user network centrality in influencing idea popularity in OICs from a social network perspective. Furthermore, by integrating social network analysis and persuasion theories, this study confirms the interaction effects of review characteristics and users’ social network centrality on idea popularity.

This study’s results highlight that users should actively interact and share with reviewers their professional product design knowledge and/or the journey of their design to improve the volume of reviews on their user designs. Moreover, users could also draw more attention from other users by actively responding to heterogeneous reviews. In addition, users should be cautious with the number of people they follow and ensure that they improve their in-degree rather than out-degree centrality in their social networks.

This study integrates social network analysis and persuasion theories to explore the effects of online reviews and users’ centrality on idea popularity in OICs, a vital research issue that has been overlooked.

Despite the availability of many metrics and tools for marketing performance measurement, the way in which firms use their marketing metrics remains underexplored. This study aims to address this gap by empirically establishing the differing effects of the diagnostic and interactive uses of marketing metrics on firms’ market-sensing capability, contingent on competitive intensity and focus on market-related metrics.

This study builds on survey data collected from 210 Irish-based firms, complemented by 21 in-depth interviews with business managers. Survey data are analysed using regression analysis.

This study finds that firms using marketing metrics interactively to communicate organizational focus are better able to sense their markets, especially under high competition. The authors observe a positive impact of the interactive use of metrics on market-sensing capability, but a U-shaped impact of their diagnostic use, the magnitudes of which further depend on competitive intensity and firms’ focus on market-related metrics.

This study provides a nuanced view of marketing performance measurement (MPM) practices within firms, particularly focussing on diagnostic versus interactive uses of marketing metrics. It also sheds further light on how two diverse uses of marketing metrics – diagnostic and interactive uses – influence a firm’s market-sensing capability. Moreover, the identification of boundary conditions also contributes to the discussion of contextuality in MPM, highlighting the importance of aligning a firm’s uses of marketing metrics with its business environment.

This study provides novel insights into how diverse uses of marketing metrics may benefit firms. The differing effects of diagnostic and interactive uses of marketing metrics on market sensing highlight a primary need for developing the latter and for using the former only with caution. It establishes that all firms would equally benefit from an interactive use of marketing metrics that is pivotal to improving their ability to anticipate, detect and sense market changes.

This study provides novel understanding of the role of marketing metric uses in firms’ market-sensing capability and contributes to the discussion of contextuality in marketing performance measurement. It highlights the importance of aligning a firm’s use of marketing metrics with its business environment.