Weiliang Zhang, Sifeng Liu, Lianyi Liu, R.M. Kapila Tharanga Rathnayaka, Naiming Xie and Junliang Du
China's population aging is gradually deepening and needs to be actively addressed. The purpose of this paper is to construct a novel model for analyzing the population aging.
Abstract
Purpose
China's population aging is gradually deepening and needs to be actively addressed. The purpose of this paper is to construct a novel model for analyzing the population aging.
Design/methodology/approach
To analyze the aging status of a region, this study has considered three major indicators: total population, aged population and the proportion of the aged population. Additionally, the authors have developed a novel grey population prediction model that incorporates the fractional-order accumulation operator and Gompertz model (GM). By combining these techniques, the authors' model provides a comprehensive and accurate prediction of population aging trends in Jiangsu Province. This research methodology has the potential to contribute to the development of effective policy solutions to address the challenges posed by the population aging.
Findings
The fractional-order discrete grey GM is suitable for predicting the aging population and has good performance. The population aging of Jiangsu Province will continue to deepen in the next few years.
Practical implications
The proposed model can be used to predict and analyze aging differences in Jiangsu Province. Based on the prediction and analysis results, identified some corresponding countermeasures are suggested to address the challenges of Jiangsu's future aging problem.
Originality/value
The fractional-order discrete grey GM is firstly proposed in this paper and this model is a novel grey population prediction model with good performance.
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Yingjie Yang, Sifeng Liu and Naiming Xie
The purpose of this paper is to propose a framework for data analytics where everything is grey in nature and the associated uncertainty is considered as an essential part in data…
Abstract
Purpose
The purpose of this paper is to propose a framework for data analytics where everything is grey in nature and the associated uncertainty is considered as an essential part in data collection, profiling, imputation, analysis and decision making.
Design/methodology/approach
A comparative study is conducted between the available uncertainty models and the feasibility of grey systems is highlighted. Furthermore, a general framework for the integration of grey systems and grey sets into data analytics is proposed.
Findings
Grey systems and grey sets are useful not only for small data, but also big data as well. It is complementary to other models and can play a significant role in data analytics.
Research limitations/implications
The proposed framework brings a radical change in data analytics. It may bring a fundamental change in our way to deal with uncertainties.
Practical implications
The proposed model has the potential to avoid the mistake from a misleading data imputation.
Social implications
The proposed model takes the philosophy of grey systems in recognising the limitation of our knowledge which has significant implications in our way to deal with our social life and relations.
Originality/value
This is the first time that the whole data analytics is considered from the point of view of grey systems.
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Md Karim Rabiul, Marianna Sigala and Rashed Al Karim
This study examines the mediating role of organizational engagement in the link between human resources management (HRM) practices and commitment to quality services (CQS). It…
Abstract
Purpose
This study examines the mediating role of organizational engagement in the link between human resources management (HRM) practices and commitment to quality services (CQS). It also investigates the moderating effect of turnover intention on the link between HRM practices and organizational engagement, and the moderating effect of employee adaptability on the link between organizational engagement and CQS.
Design/methodology/approach
Customer contact employees (N = 593) in Bangladeshi hotels were recruited using a convenient sampling method. Partial least squares structural equation modeling (PLS-SEM) was applied to test the hypotheses.
Findings
Organizational engagement significantly mediates the relationship between HRM practices and CQS. Turnover intention negatively and employee adaptability positively moderates the proposed relationships.
Practical implications
Hospitality managers may use the findings to enhance quality customer services by implementing appropriate HRM practices, reducing turnover, and increasing adaptability and organizational engagement.
Originality/value
The findings contribute to social exchange theory, theory of planned behavior, and job demand-resources theories by explaining the mediating role of organizational engagement and moderating role of turnover intention and employee adaptability which are yet to be discovered.
研究目的
本研究探討組織參與在人力資源管理實務與提供優質服務的承諾兩者之間的關聯上所扮演的協調角色。研究人員亦探究(一)離職意向在人力資源管理實務與組織參與之間的關聯上所扮演的調節角色,以及(二)員工適應性在組織參與與提供優質服務的承諾兩者之間的關聯上所扮演的調節角色。
研究設計
研究人員以方便抽樣方法招募於孟加拉的酒店工作的員工 (N = 593) (593人),他們均為第一線服務員工。研究人員繼而使用結構方程模型 (PLS-SEM) 去測試各項假設。
研究結果
研究結果顯示,組織參與會顯著地調節人力資源管理實務與提供優質服務的承諾兩者之間的關聯。而且,離職意向在人力資源管理實務與組織參與之間的關聯上所起的調節作用是負面的; 相反地,員工適應性在組織參與與提供優質服務的承諾兩者之間的關聯上所起的調節作用則是肯定的。
研究的新穎性
研究結果闡明了(一)組織參與的調節角色; (二)離職意向的調節角色; 以及(三)員工適應性的調節角色。這些調節角色尚待探索; 就此而言,研究結果對社會交換論、計劃行為理論和工作要求-資源理論三者均具貢獻。
研究帶來的啟示
接待業的管理人員可藉著研究結果去提高客戶服務質量,方法是透過實施合適的人力資源管理措施、降低離職意向和增強組織適應性和組織參與。
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Michael Wang, Bill Wang and Ricky Chan
Due to increasing supply chain complexity, the supply chain uncertainty has become an imperative issue, which hinders the development of modern logistics and supply chain…
Abstract
Purpose
Due to increasing supply chain complexity, the supply chain uncertainty has become an imperative issue, which hinders the development of modern logistics and supply chain management. The paper attempts to conceptualize reverse logistics uncertainty from supply chain uncertainty literature and present the types of reverse logistics uncertainty in a triadic model.
Design/methodology/approach
The concept of reverse logistics uncertainty is developed based on a triadic model of logistics uncertainty and supply chain uncertainty literature. A desk research is conducted to develop a taxonomy of reverse logistics uncertainty. To better depict the reverse logistics uncertainty, we use case studies to discuss the types of reverse logistics uncertainty in the triadic model.
Findings
The study reveals four types of supply chain uncertainties in the reverse logistics. We call them reverse logistics uncertainty. Type-A and Type-B uncertainty are new types of supply chain uncertainty in the reverse logistics.
Research limitations/implications
The types of reverse logistics uncertainty have not been empirically validated in industries. Especially, the two new types including Type-A and Type-B reverse uncertainty need further exploration.
Originality/value
Although reverse logistics has been discussed in the past decades, very few studies have been conducted on the supply chain uncertainty in returns management arena. The paper offers valuable insights to better understand the supply chain uncertainty in the reverse logistics. This also provides suggestions for both managers and researchers to reflect on the reverse logistics uncertainty management and business sustainability.