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This paper presents neural network‐based recognition system for automatic light emitting diode (LED) inspection. The back‐propagation neural network (BPNN) is proposed and tested. The current‐voltage (I‐V) characteristic data of LED from the inspection process is used for the network training and testing. This study selects 300 random samples as network training and employs 100 samples as network testing. The experimental results show that if the classification work is doen well, the accuracy of recognition is 100 per cent, and the testing speed of the proposed recognition system is amost one half faster than the traditional inspection system does. The proposed neural‐network approach is successfully demonstrated by real data sets and can be effectively developed as a recognition system for a practical application purpose.

The IC packaging industry heavily relies on shop floor information, necessitating the development of a model to flexibly define shop floor information and timely handle manufacturing data. This study presents a novel data model of product manufacturing flow to define shop floor information to effectively respond to accelerated developments in IC package industry. The proposed data model consists of four modules: operation template setup, general process setup, enhanced bill of manufacture (EBOMfr) setup, and work‐order process setup. The data model can flexibly define the required shop floor information and decision rules for shop floor product manufacturing flow, allowing one to easily adopt changes of the product and on the shop floor. However, to handle floor dynamics of the ICD packaging industry, this work also proposes a WIP (i.e. work‐in‐process) system for monitoring and controlling the product manufacturing flow on the shop floor. The WIP system integrates the data model with a WIP execution module. Furthermore, an illustrative example, the MIRL WIP System, developed by Mechanical Industrial Research Laboratories of Industrial Technology Research Institute, demonstrates the effectiveness of the proposed model.

Due to the advancement of technology and rapidly changing environment of the market, the life cycle of high‐tech products is becoming shorter. The enterprise must constantly innovate and select correct development strategy of new product in order to respond to customers’ demands for upgrading operational performance of industry. Development of new product is the critical activity for enterprise’s survival and growth. This research focuses on the effects of Taiwan high‐tech companies’ introduction of innovative activity and development strategy of new product on development performance of new product for analysis and exploration. The result findings reveal that: (1) High execution degree of innovative activity has positive effect on the implementation of development strategy of new product; (2) The companies with better implementation of development strategy of new product reveal better development performance; (3) The companies with higher degree of execution of innovative activity and better execution of development strategy of new product reveal better development performance of new product.

Consumer-generated online product reviews (OPRs) have become a crucial source of information for consumers; however, OPRs are increasingly being incentivized. The purpose of this paper is to find a method of sponsorship and disclosure that could be considered ethically sound.

This study adopted a quasi-experimental approach to clarifying how the method of sponsorship impacts reader perceptions of OPRs in terms of helpfulness, credibility and purchase intention. Two experiments were performed on an online platform using data from 480 participants. Hypotheses were tested using analysis of covariance.

Meaning under the premise that sponsorship information is disclosed and not withheld from the readers, Study 1 revealed that experiential sponsorship is the best sponsorship. Study 2 revealed that featuring reviewers with greater influence in the online community increases the positive influence of disclosing experiential sponsorship on OPR persuasiveness.

The findings in this study provide rational incentives for firms to disclose sponsorship information, i.e. demonstrate high ethical standards in marketing. This was shown to create a win-win-win situation for consumers, firms and reviewers. Managerial implications for online marketing managers are also discussed.

This research explores the complex interplay of multiple social factors with regard to what might encourage or inhibit users to interact with social commerce (SC).

To investigate the phenomenon, we developed a model based on goal-directed behaviour and pluralistic ignorance theory (typically generated by universal behavioural adherence to social norms). Based on the 394 valid responses collected from a survey, partial least squares structural equation modelling (PLS-SEM), PROCESS and ANOVA were employed to examine the research hypotheses.

The results show that pluralistic ignorance and commercial desire positively influence SC intention. More importantly, our results show that the moderating effect of pluralistic ignorance dampens the positive relationship between social subjective norms and commercial desire. The findings also suggest that pluralistic ignorance mediates the relationships between: (1) social identity and SC intentions and (2) fear of isolation and SC intentions.

Consequently, this study reveals that SC intentions result from complex interactions between an individual’s psychology and social phenomena. Theoretical and managerial implications are also discussed to provide for the successful development of strategies regarding SC for researchers and SNSs operators.

Stimulated by trends in group purchasing and online social communities, consumers are changing their shopping behavior and increasingly turning to websites for their shopping needs. The purpose of this paper is to investigate how website quality influences shopping websites to create value for the customer and promote loyalty among customers, as well as moderating effects of online shopping experience.

This study collected data from 275 respondents for testing against the proposed research model by means of the partial least squares (PLS) path modeling. ADANCO software was used to assess the reliability and validity of the measurement model, conduct an analysis of the goodness of model fit for the overall model, and test the hypotheses through structural modeling.

Empirical results demonstrate that system quality and electronic service quality (e-service quality) have a significant positive effect on the perceived value of consumer/seller relationship; the perceived value of the consumer/seller relationship has a significant positive effect on online loyalty; online shopping experience does not exert a moderating effect on the relationship between website quality and the perceived value of consumer/seller relationship.

This study applied the PLS path modeling approach using ADANCO variance-based structural equation modeling software to verify that website quality plays an important role in distinguishing a brand from other brands in e-tailing, making it an essential factor of a shopping website’s business success. This study further verified that the amount of previous online shopping experience a consumer has does not interfere with the positive influence that website quality exerts on the perceived value of the consumer/seller relationship. The above indicates that it is imperative for website managers to adopt online shopping experience of consumers as a market segmentation variable so as to enhance website quality, increase the perceived value of consumer-seller relationships, and win consumer loyalty.

Set in an emerging economy context, the purpose of this paper is to examine the determinants of green consumers’ purchase behavior on organic food by analyzing the impact of word-of-mouth (WOM) effects (i.e. tie strength, sender’s green expertise, receiver’s green expertise), conformity behaviors (i.e. normative interpersonal influence and informational interpersonal influence) on green purchase intention, and the relationship between green purchase intention and green purchase behavior.

Data were collected by self-administered questionnaire completed by respondents who had purchase experience of organic food in the last six months. The specific context of this study is green consumption for organic food in Taiwan. Data collection was implemented in a convenience sampling method. Among the 578 consumers who had filled the questionnaire, 147 did not have any purchase history of organic food, resulting in a final usable sample of 431 (response rate 74.57 percent) in Taiwan. The data were collected during a five-week period in late 2015.

Through structural equation modeling analysis, data were analyzed and the empirical results indicate that tie strength, sender’s green expertise, and receiver’s green expertise have a positive influence on green consumer’s susceptibility to informational interpersonal influences and normative interpersonal influences, separately. In addition, informational interpersonal influences and normative interpersonal influences both have a positive relationship on green purchase intention, which will further positively influence the green purchase behavior.

This study reminds marketers of the impact of WOM effects as well as interpersonal influences on consumers. It examines the impact of tie strength, senders’ green expertise, and receivers’ green expertise on green purchase intention and green purchase behavior. This study also explores the mediation effects of green consumers’ susceptibility to interpersonal influences. Consumers’ susceptibility to interpersonal influence is discussed in the marketing literature. However, few prior studies have explored its effect in the green setting. Last, few attempts have discussed the relationship between green purchase intention and green purchase behavior. This study contributes to the literature by examine the relationship between green purchase intentions and green purchase behavior.

This study aims to understand the epistemic foundation of the classification applied in the first Chinese library catalogue, the Seven Epitomes (Qilue).

Originating from a theoretical stance that situates knowledge organization in its social context, the study applies a multifaceted framework pertaining to five categories of textual data: the Seven Epitomes; biographical information about the classificationist Liu Xin; and the relevant intellectual, political, and technological history.

The study discovers seven principles contributing to the epistemic foundation of the catalogue's classification: the Han imperial library collection imposed as the literary warrant; government functions considered for structuring texts; classicist morality determining the main classificatory structure; knowledge perceived and organized as a unity; objects, rather than subjects, of concern affecting categories at the main class level; correlative thinking connecting all text categories to a supreme knowledge embodied by the Six Classics; and classicist moral values resulting in both vertical and horizontal hierarchies among categories as well as texts.

A major limitation of the study is its focus on the main classes, with limited attention to subclasses. Future research can extend the analysis to examine subclasses of the same scheme. Findings from these studies may lead to a comparison between the epistemic approach in the target classification and the analytic one common in today's bibliographic classification.

The study is the first to examine in depth the epistemic foundation of traditional Chinese bibliographic classification, anchoring the classification in its appropriate social and historical context.

The purpose of this study is to investigate a framework for knowledge retention to support business continuity in cross-border mergers of the telecommunications industry in Lesotho.

This study applied a qualitative case study, with data collected through interviews from a purposively selected sample of staff members who held managerial positions. Information in this study was partially extracted from the PhD thesis of Dr Tseole ET supervised by Prof Ngulube P at the University of South Africa completed in 2021.

The study discovered that a considerable amount of knowledge may have been lost because employees who either left the organisation or those who were apparently forced to resign during the process had left without any proper knowledge retention arrangements.

The framework proposed in this study may be used in framing future studies as a theoretical framework. The study also provides new literature for review and discussion of background in future related studies.

The framework provided in the study may be used as a benchmark in the knowledge management industry and/or organisations for policy development or improvements and implementation of knowledge retention strategies.

Through recommendations and framework provided by this study, organisations will be able to improve their services to their sphere of influence in the surrounding communities. So, community will be receiving an improved and good service at all the times.

A framework for facilitating knowledge retention in the cross-border mergers of the telecommunications industry is therefore proposed and the researchers believe it will be helpful to the organisation for improving knowledge retention going forward, particularly in the merger process.

Artificial intelligence (AI) will be performing 52% of the tasks in companies by 2025. The increasing adoption of AI is generating technological turbulence in the business environment. Previous studies have also shown that employees are aware of the high risk of losing their jobs when being replaced by AI. The risk of employees engaging in opportunistic behaviors, such as knowledge hiding, is thus fairly high. Therefore, the aim of this paper is to analyze the mediating effect of employee’s AI awareness on the relationship between technological turbulence generated by AI and the three types of knowledge hiding: evasive hiding, playing dumb and rationalized hiding.

Structural equations by the partial least squares method were used to test the proposed research model.

The most interesting finding is that employee’s AI and robotics awareness fulfills almost all mediating functions in the relationship between technological turbulence generated by AI and the three types of knowledge hiding.

The results show that knowledge hiding in the digital age is first and foremost a strategy by employees to sabotage and induce failure in process automation, to reduce the risk of being replaced in the workplace by AI. This study indicates that employees are willing to hide knowledge in all possible ways when perception that AI is a threat to their job increases. In other words, technological turbulence generated by AI and employee’s AI awareness are the two great new triggers of knowledge hiding in the digital age.