This study investigated how Generation Z adopted brand messages through trending topics and analysed the central and peripheral routes of information adoption. It explored the…
Abstract
Purpose
This study investigated how Generation Z adopted brand messages through trending topics and analysed the central and peripheral routes of information adoption. It explored the roles of informational and emotional supports in influencing information adoption through perceived information usefulness and considered the adoption of brand messages within trending topic discussions.
Design/methodology/approach
Drawing on the extension information adoption model, this study employed a quantitative approach by utilising covariance-based structural equation modelling to analyse 400 valid web-based questionnaire responses from Sina Microblog users among Generation Z in China.
Findings
Adopting brand messages via trending topics, with cues emphasising information quality as the central route and information credibility as the peripheral route, enhances perceived information usefulness. Notably, Generation Z can derive informational and emotional support from trending topic discussions, influencing their perceived information usefulness. This process operates independently of the dual routes of information adoption.
Research limitations/implications
Marketers can leverage influencers and users’ comments to motivate Generation Z to adopt brand messages through trending topics, but this study was limited by the demographic diversity of its sample and the specific types of brands analysed. Incorporating cross-cultural comparisons, group analyses, potential moderating factors and control variables could improve the model’s generalisability.
Originality/value
Compared to information adoption models rooted in the organisational information exchange, the originality of this study lies in confirming that, within the context of trending topics, which blend social connections with an anonymous environment, informational and emotional supports can serve as additional cues influencing brand information adoption via perceived information usefulness.
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This study employs bibliometric analysis to map the research landscape of social media trending topics during the COVID-19 pandemic. The authors aim to offer a comprehensive…
Abstract
Purpose
This study employs bibliometric analysis to map the research landscape of social media trending topics during the COVID-19 pandemic. The authors aim to offer a comprehensive review of the predominant research organisations and countries, key themes and favoured research methodologies pertinent to this subject.
Design/methodology/approach
The authors extracted data on social media trending topics from the Web of Science Core Collection database, spanning from 2009 to 2022. A total of 1,504 publications were subjected to bibliometric analysis, utilising the VOSviewer tool. The study analytical process encompassed co-occurrence, co-authorship, citation analysis, field mapping, bibliographic coupling and co-citation analysis.
Findings
Interest in social media research, particularly on trending topics during the COVID-19 pandemic, remains high despite signs of the pandemic stabilising globally. The study predominantly addresses misinformation and public health communication, with notable focus on interactions between governments and the public. Recent studies have concentrated on analysing Twitter user data through text mining, sentiment analysis and topic modelling. The authors also identify key leading organisations, countries and journals that are central to this research area.
Originality/value
Diverging from the narrow focus of previous literature reviews on social media, which are often confined to particular fields or sectors, this study offers a broad view of social media's role, emphasising trending topics. The authors demonstrate a significant link between social media trends and public events, such as the COVID-19 pandemic. The paper discusses research priorities that emerged during the pandemic and outlines potential methodologies for future studies, advocating for a greater emphasis on qualitative approaches.
Peer review
The peer-review history for this article is available at: https://publons.com/publon/10.1108/OIR-05-2023-0194.
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Hsin-Hui Lin, Wan-Chu Yen, Yi-Shun Wang and Yen-Min Yeh
The purpose of this paper is to explore the effects of consumer role (involved vs observing) on consumer responses in the context of online group buying (OGB) service failures.
Abstract
Purpose
The purpose of this paper is to explore the effects of consumer role (involved vs observing) on consumer responses in the context of online group buying (OGB) service failures.
Design/methodology/approach
A scenario simulation method with a 2×3 factorial design was used to investigate the impact of consumer role (i.e. involved consumers and observing consumers) on consumer responses (i.e. perceived quality, negative electronic word-of-mouth (eWOM), and switching intention). The moderating role of seller offering type (i.e. physical products, true services, and pseudo services) on the relationship between the consumer role and responses was also tested.
Findings
The differences in perceived quality, negative eWOM, and switching intention between involved consumers and observing consumers were significant. Further, seller offering type moderated the relationship between consumer role and consumer response.
Practical implications
These findings provide several important theoretical and practical implications in regard to OGB service failure and recovery.
Originality/value
This study enriches OGB and service failure literature by a pioneering investigation of how consumer roles respond to OGB service failures and how different seller offering types influence the relationship between consumer role and consumer response. The results will help service providers of OGB benefit from enhancing their service recovery strategies to cope with OGB service failures.
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Yi Yang, Jing Zhao and Young Soo Yang
This study investigates two internationalization strategies, foreign direct investment (FDI) expansion and export expansion, and their effects on the innovation performance of…
Abstract
Purpose
This study investigates two internationalization strategies, foreign direct investment (FDI) expansion and export expansion, and their effects on the innovation performance of Chinese multinational enterprises (MNEs). Additionally, it explores the moderating roles of both formal and informal political connections in the relationship between these internationalization strategies and innovation performance.
Design/methodology/approach
The hypotheses were tested using the Poisson panel model and data on 2,106 observations from 645 Chinese-listed firms between 2010 and 2017.
Findings
FDI expansion significantly enhances the innovation performance of Chinese MNEs compared to export expansion. Moreover, formal and informal political connections are found to have distinct moderating effects: formal political connections amplify the positive effect of FDI expansion on firm innovation, whereas informal political connections tend to weaken it.
Originality/value
This study contributes to the discourse on innovation and political connections, especially in the context of EMNEs. It enriches the theoretical understanding of internationalization strategies and innovation performance in EMEs, contrasting with the technology-utilization motives observed in MNEs from developed economies.
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Anas Al-Refaie, Ali Alashwal, Zulkiflee Abdul-Samad, Hafez Salleh and Ahmed Elshafie
Weather is one of the main factors affecting labour productivity. Existing weather-productivity models focussed on hot and cold climates paying less attention to the tropics. Many…
Abstract
Purpose
Weather is one of the main factors affecting labour productivity. Existing weather-productivity models focussed on hot and cold climates paying less attention to the tropics. Many tropical countries are expected to be the most areas affected by accelerated climate change and global warming, which may have a severe impact on labour health and productivity. The purpose of this paper is to assess whether the existing models can be used to predict labour productivity based on weather conditions in the tropics.
Design/methodology/approach
Five models are identified from the literature for evaluation. Using real labour productivity data of a high-rise building project in Malaysia, the actual productivity rate was compared with predicted productivity rates generated using the five models. The predicted productivity rates were generated using weather variables collected from an adjusting weather station to the project.
Findings
Compared with other models evaluated in this paper, the United States Army Corps of Engineers (USACE) was found to be the best model to predict productivity based on the case study data. However, the result shows only a 57% accuracy level of the USACE model indicating the need to develop a new model for the tropics for more accurate prediction.
Originality/value
The result of this study is perhaps the first to apply meteorological variables to predict productivity rates and validate them using actual productivity data in the tropics. This study is the first step to developing a more accurate productivity model, which will be useful for project planning and more accurate productivity rate estimation.
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Suggests that misunderstandings frequently occur when trying to understand Chinese language and culture, and so gives the implied meaning of various Chinese expressions and…
Abstract
Suggests that misunderstandings frequently occur when trying to understand Chinese language and culture, and so gives the implied meaning of various Chinese expressions and sayings such as greetings, thanks, respect, age, congratulations and taboo subjects.
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Peng Jiang, Wenbao Wang, Yi-Chung Hu, Yu-Jing Chiu and Shu-Ju Tsao
It is challenging to derive an appropriate tolerance relation for tolerance rough set-based classifiers (TRSCs). The traditional tolerance rough set employs a simple distance…
Abstract
Purpose
It is challenging to derive an appropriate tolerance relation for tolerance rough set-based classifiers (TRSCs). The traditional tolerance rough set employs a simple distance function to determine the tolerance relation. However, such a simple function does not take into account criterion weights and the interaction among criteria. Further, the traditional tolerance relation ignores interdependencies concerning direct and indirect influences among patterns. This study aimed to incorporate interaction and interdependencies into the tolerance relation to develop non-additive grey TRSCs (NG-TRSCs).
Design/methodology/approach
For pattern classification, this study applied non-additive grey relational analysis (GRA) and the decision-making trial and evaluation laboratory (DEMATEL) technique to solve problems arising from interaction and interdependencies, respectively.
Findings
The classification accuracy rates derived from the proposed NG-TRSC were compared to those of other TRSCs with distinctive features. The results showed that the proposed classifier was superior to the other TRSCs considered.
Practical implications
In addition to pattern classification, the proposed non-additive grey DEMATEL can further benefit the applications for managerial decision-making because it simplifies the operations for decision-makers and enhances the applicability of DEMATEL.
Originality/value
This paper contributes to the field by proposing the non-additive grey tolerance rough set (NG-TRS) for pattern classification. The proposed NG-TRSC can be constructed by integrating the non-additive GRA with DEMATEL by using a genetic algorithm to determine the relevant parameters.
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Florence Yean Yng Ling and Eunice Jing Yi Lew
Generation Z built environment (BE) undergraduates and graduates (Zoomers) are the latest cohort entering the job market. Existing research has yet to comprehensively explore…
Abstract
Purpose
Generation Z built environment (BE) undergraduates and graduates (Zoomers) are the latest cohort entering the job market. Existing research has yet to comprehensively explore approaches for attracting and engaging Zoomer employees within the BE sector. This study aims to identify effective strategies for recruiting and retaining Zoomers in the BE sector.
Design/methodology/approach
A mixed-methods research design comprising survey and interviews with Zoomers was employed. Data were collected from Zoomers via an online survey using a structured questionnaire and interviews.
Findings
The first finding, job flexibility, is the most important job motivator. Zoomers seek hybrid work arrangements, and a mix of fieldwork and desk bound work. The second finding, “earned media” (and not “owned media”), is an important way to attract Zoomers. As savvy digital natives, Zoomers rely on reviews about the organization posted on independent online platforms or employees’ own social media accounts. The third finding is the diminishing role of family in Zoomers’ decision-making about their careers.
Research limitations/implications
The findings are limited to Zoomers’ views about recruitment and retention within the BE sector.
Practical implications
Recommendations are offered to organizations on strategic job redesign and increasing “earned media” to attract Zoomers.
Originality/value
The findings contribute to understanding Zoomers’ approach to recruitment and retention based on Herzberg’s motivation-hygiene theory. Herzberg’s hygiene factors, which are essential benefits such as salary and career progression, remain important. The novel finding is the discovery of specific human resource (HR) practices that Zoomers consider to be hygiene factors, whereas older generations view them as “good-to-have” motivators. This underscores the intergenerational divergence in attitudes towards recruitment and retention in the BE sector.
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Guizhi Wang, Jing Zhao and Jibo Chen
The purpose of this paper is to extend two‐dimensional sequential uniform design and present three‐dimensional sequential uniform design which can optimize the problem of…
Abstract
Purpose
The purpose of this paper is to extend two‐dimensional sequential uniform design and present three‐dimensional sequential uniform design which can optimize the problem of determining the extreme value of three‐factor polynomial.
Design/methodology/approach
Since there are limitations in two‐dimensional sequential uniform design, three‐dimensional sequential uniform design introduced in this paper is to arrange the experimental points by U9(93) uniform design table and to determine the maximum of the experimental values according to the demand. It is proven that the convergence of the experimental central point's sequence and that it can optimize the problem of determining the extreme value of no‐cross term quadratic polynomial monotone function class and the corresponding conditions are also proven. Taking the no‐cross term quadratic polynomial monotone function as an example, the superiority of it is testified.
Findings
Three‐dimensional sequential uniform design can optimize the problem of determining the extreme value of three‐factor polynomial. It can get higher precision and better convergence but do fewer experiments than general uniform design.
Practical implications
A very effective method in resolving the problem of selecting optimum on multi‐dimensional space.
Originality/value
A new method of three‐dimensional sequential uniform design which can get higher precision and better convergence is presented.
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Jing Yi Yong, M.-Y. Yusliza, Charbel Jose Chiappetta Jabbour and Noor Hazlina Ahmad
Green human resource management (HRM) has been considered to be a vitally important mechanism for companies to move towards a sustainable organization. By adopting the…
Abstract
Purpose
Green human resource management (HRM) has been considered to be a vitally important mechanism for companies to move towards a sustainable organization. By adopting the Ability-Motivation-Opportunity as the underpinning theory, the purpose of this paper is to identify the factors that facilitate the adoption of Green HRM in Malaysia.
Design/methodology/approach
A qualitative exploratory approach research was adopted in this study. The required data for this study were collected using semi-structured face-to-face interviews with human resources directors and managers from four large manufacturing companies in Malaysia. The data collected was then reorganized into four themes.
Findings
Based on the interview, four key factors that influence the adoption of Green HRM include stakeholder pressures, relative advantage, which means the perceived benefits from implementing Green HRM, top management commitment and green intellectual capital, which means the intellectual capital incorporating green innovation or environmental management. Surprisingly, among the three dimensions of green intellectual capital, only green human capital and green structural capital were greatly discussed by the human resources directors and managers, while the role of green relational capital on the adoption of Green HRM was hardly observed.
Originality/value
Research studies on Green HRM in Malaysia are scarce. The originality of this paper lies in its exploration of Green HRM in an environmental sensitive sector and the insight it provides to academics and practitioners involved in the manufacturing sector. Although research findings cannot be generalized, they can be used as insights for both academics and end-users in emerging economies.