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The purpose of this study is to propose and examine an integrated learning model for improving training effectiveness in workplace learning. Specifically, this study investigated the effect of achievement goal-setting intervention across three groups of new employees from a multinational medical company. During a three-day remote training program, the role of each achievement goal orientation (AGO) in goal setting intervention and their relations with trainees’ applied learning strategies were examined. This study proposed and validated an integrated training model for improving remote workplace learning effectiveness.

This study was based on two data sources, the pre- and posttests scores; time on task (deep learning: completing reflective practice) and time on content learning (surface learning: watching tutorials) retrieved from an adaptive learning platform. A total number of 133 participants were recruited in this study, and they were randomly assigned to three interventional groups. The intervention was grounded from the AGO theory and goal setting theory. A series of statistical analysis were conducted to examine the effect of each type of achievement goal setting as a prompt for new employees’ learning behavior and performance.

Results indicated that setting mastery goal at the beginning of the training program leads to productive learning outcomes. Compared with the groups being required to set performance goal (final rank) or not to set any goal for the training purpose, trainees’ who were assigned to set a mastery goal (final performance score) performed statistically significantly higher than the other groups. Additionally, learners who set mastery goal spent higher proportion of time on deep learning than learners from the other groups. The results proved mastery goal setting as an effective prompt for boosting workplace learning effectiveness.

Organizations and institutions can take setting mastery approach goals as a prompt at the beginning of the training to increase learning effectiveness. In this way, trainees are promoted to apply more deep learning strategies and achieve better learning outcomes while setting mastery goal for their training purpose.

To the best of the authors’ knowledge, this study was the first to combine the intervention of goal setting and types of AGOs into workplace learning. This study adds to previous research on goal setting theory and AGO theory for the practical application and proposes an effective model for learners’ adaptive remote learning. Findings of this study can be used to provide educational psychological insights for training and learning in both industrial and academic settings.

This paper aims to review the latest management developments across the globe and pinpoint practical implications from cutting-edge research and case studies.

This briefing is prepared by an independent writer who adds their own impartial comments and places the articles in context.

The positive impact of training can be enhanced if learners set appropriate goals at the outset. By opting to pursue a mastery goal, learners are likely to engage more with the deep learning strategies that are associated with a broader range of desirable outcomes for both learners and their organization.

The briefing saves busy executives and researchers hours of reading time by selecting only the very best, most pertinent information and presenting it in a condensed and easy-to-digest format.

This paper aims to review the latest management developments across the globe and pinpoint practical implications from cutting-edge research and case studies.

This briefing is prepared by an independent writer who adds their own impartial comments and places the articles in context.

Emphasis on achievement goal orientation can enable firms to realize key earning outcomes from workplace training. Desired outcomes become considerably likelier when learners set a mastery-approach goal as opposed to other goal types at the outset of training.

The briefing saves busy executives, strategists and researchers hours of reading time by selecting only the very best, most pertinent information and presenting it in a condensed and easy-to-digest format.

Drawing on self-determination theory (Deci and Ryan, 2012) and Hew’s (2016) five-factor model, our study aimed to investigate the impact of two online training design factors (instructor accessibility and active learning) on learner’s self-efficacy and learning outcome amid the COVID-19 pandemic.

A randomized pretest-posttest control group field experiment was designed to assess participants’ self-efficacy and learning outcome of an online training program - territory business management plan, under three conditions: instructor accessibility, active learning, and controlled. Participants (N=87) were medical sales representatives from a Fortune-Global 500 pharmaceutical company’s subsidiary office in China. Data was analyzed with 2 (time) x 3 (group) MANOVA with time (pretest and posttest) as a repeated measure to investigate differences in changes in self-efficacy and learning outcome between three groups.

Overall, participants’ self-efficacy and learning outcome were significantly improved via the online training program for all three groups. Specifically, the impact of the training on learning outcome was the strongest for the active learning group, less strong for the instructor accessibility group, and the least strong for the control group.

Our research contributes towards understandings of the effectiveness of online talent training programs by examining two critical instructional design factors during a time of crisis. Our findings suggest that active learning (interactions with the training materials by purposeful self-reflection) might be a stronger predictor for increasing learning outcome than instructor accessibility (receiving feedback and tutoring sessions from the instructor) for online training programs.

Banking is the key industry to guarantee the core leading role of finance in the process of economic development. It is important to study the bank efficiency and optimal allocation of bank’s resources. The purpose of our paper is to study the optimal allocation of resources between the bank savings system and loan system under the premise of environmental heterogeneity.

We use a two-stage meta-frontier Data Envelopment Analysis model to solve the relative efficiency of each city branch and use the multivariate statistical tools to analyze the empirical results.

This paper measures the relative efficiency of 16 Bank Branches of a state-owned bank in Anhui province considering regional heterogeneity. Based on the optimal resource allocation, we get the two-stage operation performance of all banks under group-frontier and meta-frontier and analyze the impact of the technical differences between the branches.

This study has a positive guiding significance for the banking industry to improve its operational efficiency in various business practices in the new era of big data. It will also provide practical suggestions and support for the government and relevant departments in the process of formulating macro-policies to ensure the healthy and stable development of the banking industry.

With an increasingly fierce competition of the shipbuilding industry, advanced technologies and excellent management philosophies in the manufacturing industry are gradually introduced to domestic shipyards. The purpose of this study is to promote the lean management of Chinese ship outfitting plants by lean production strategy.

To promote the lean implementation of Chinese shipyards, the lean practice of ship-pipe part production is highlighted by lot-sizing optimization and strategic CONWIP (constant work-in-process) control. A nonlinear programming model is formulated to minimize the total cost of ship-pipe part manufacturing and the particle swarm optimization (PSO)-based algorithm is designed to resolve the established model. Besides, the pull-from-the-bottleneck (PFB) strategy is used to control ship-pipe part production, verified by Simulink simulation.

Results show that the proposed lean strategy of the programming model and strategic PFB control could assist Chinese ship outfitting plants to leverage competitive advantage by waste reduction and lean achievement. Specifically, the PFB double-loop control strategy shows better performance when there is high productivity and the PFB single-loop control outperforms at lower productivity scenarios.

To verify the effectiveness of the proposed lean strategy, a case study is performed to validate the formulated model. Also, simulation experiments realized by FlexSim software are conducted to testify results obtained by the constructed programming model.

Lean production management practice of the shipyard building industry is performed by the proposed lean production strategy through lot-sizing optimization and strategic PFB control in terms of ship-pipe part manufacturing.

The booming of the Internet of things (IoT) and artificial intelligence (AI) techniques contributes to knowledge adoption and management innovation for the healthcare industry. It is of great significance to transport the medical resources to required places in an efficient way. However, it is difficult to exactly discover matched transportation resources and deliver to its destination due to the heterogeneity. This paper studies the medical transportation resource discovery mechanism, leading to efficiency improvement and operational innovation.

To solve the transportation resource semantic discovery problem under the novel cloud environment, the ontology modelling approach is used for both transportation resources and tasks information modes. Besides, medical transportation resource discovery mechanism is proposed, and resource matching rules are designed including three stages: filtering reasoning, QoS-based matching and user preferences-based rank to satisfy personalized demands of users. Furthermore, description logic rules are built to express the developed matching rules.

An organizational transportation case is taken as an example to describe the medical transportation logistics resource semantic discovery process under cloud medical service scenario. Results derived from the proposed semantic discovery mechanism could assist operators to find the most suitable resources.

The case study validates the effectiveness of the developed transportation resource semantic discovery mechanism, contributing to knowledge management innovation for the medical logistics industry.

To improve task-resource matching accuracy under cloud scenario, this study develops a transportation resource semantic discovery procedure from the viewpoint of knowledge management. The novel knowledge management practice contributes to operational management of the cloud medical logistics service by introducing ontology modelling and creative management.

The purpose of this paper is to explore recent national human resource development (NHRD) practices in China through a literature review focusing on programs and activities that represent the roles and interactions among the government, industry and universities.

To effectively consolidate previous work and conceptualize the recent development of the NHRD practices in China, a semi-narrative literature review was used to explore and analyze NHRD-related functions and activities.

Findings from the literature review showed that although the central government still plays a predominant role in China, universities and corporations are increasingly playing a critical role in developing an innovative and skilled workforce. At the regional level, NHRD initiatives in China have been increasingly undertaken by universities, industry and government–industry–university collaborations. The authors also found a disparity between developed and underdeveloped regions in terms of NHRD in China.

This study used the triple helix model as a framework that provides an insightful lens for researchers to examine how various social entities interact with each other and jointly contribute to NHRD. Further case studies are needed to generate evidence-based knowledge to the NHRD literature.

A more systematic NHRD leadership structure at both the national and local level is desired to unleash the potential of bottom-up development and active government–industry–university collaboration. To counter regional divergence in NHRD in China, intra- and cross-regional collaborations are helpful in improving resources distribution and workforce development.

Based on open system theory, this study focused on programs and activities that represent the roles and interactions among the government, industry and university in Chinese NHRD through the lens of the triple helix model. In addition, this study offers a conceptual model of Chinese NHRD to help scholars and practitioners understand the transitional efforts in NHRD.

Social commerce platforms are prevalent in the explosion of social media and e-commerce, and they enable conversations across a broad range of topics. However, their success depends on consumers' willingness to invest their time, attention and money. Digital influencers have shown prominent effects on consumers in those social commerce platforms. This study, thus, aims to attempt to unravel the role of digital influencers in affecting consumer engagement and purchase behaviour in online social commerce communities.

A mixed approach with a field interview, an online survey and secondary archive data are presented to confirm all the hypotheses.

Several forms of social power from digital influencers (including expert power, informational power, referent power and legitimate reciprocity power) could influence consumer engagement behaviours (including content participation and content creation). Moreover, the two types of consumer engagement behaviours could further influence consumer purchase likelihood in the social commerce community.

Several forms of social power from digital influencers (including expert power, informational power, referent power and legitimate reciprocity power) could affect consumer engagement behaviours (including content participation and content creation). Moreover, the two types of consumer engagement behaviours could further affect consumer's purchase expenditure in the social commerce community.

This study draws on the theories of social power and social influence and integrates the literature on consumer engagement to explain how digital influencers affect consumer engagement and their purchase behaviour in an online social commerce community. Firstly, this work extends existing studies on the antecedents of consumer engagement in the social commerce communities by considering the role of digital influencers. Secondly, this research advances the theoretical understanding of the influence of digital influencers through a new lens of social power. The findings also contribute to community managers, users who pursue popularity and companies who target business goals.

The success of social commerce depends on consumers' willingness to participate in social commerce activities. Practitioners have attached increasing attention to facilitating social commerce intention with influencer strategies. However, theoretical understanding or empirical investigation on the impact of digital influencers on consumers' social commerce intention is limited. This study aims to provide new insights into the drivers of two forms of social commerce intention: social shopping and social sharing intention. Based on the theoretical lens of social power, this study answers how digital influencers affect consumer satisfaction and ultimately boost their intention to conduct social commerce activities.

A field interview is conducted to determine the appropriate social power forms. An online survey on a large social commerce site in China with 310 respondents is conducted to test the proposed model.

Results indicate that expert power and referent power derived from digital influencers predict most of the consumers' economic satisfaction, whereas referent power and reciprocity power explain consumers' social satisfaction. Economic satisfaction affects social shopping and social sharing intention, whereas social satisfaction only influences social sharing intention.

This study sheds new light on the theoretical understanding of the effect of digital influencers through a lens of social power. It provides new insight into the determinants of social commerce intention. It also compensates for the neglect of social satisfaction in the social commerce context.