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1 – 4 of 4Le Bo and Xiaoli Yang
Consumers' willingness to pay premium (WTPP) for two different types of agricultural brand labels (enterprise and regional), are evaluated through a non-hypothetical Random n…
Abstract
Purpose
Consumers' willingness to pay premium (WTPP) for two different types of agricultural brand labels (enterprise and regional), are evaluated through a non-hypothetical Random n-price auction experiment during the online purchase of fresh agricultural products. The purpose of this paper is to evaluate the two WTPP, compare their differences, and explore their sustainability.
Design/methodology/approach
Data were collected in July–August 2020 from a sample of 310 consumers in Liaoning Province, China. A nonhypothetical random n-price auction experiment was implemented in a simulated online shopping environment.
Findings
The results show that WTPP exists, and WTPP level of regional brand labels is higher than that of enterprise brand labels. Consumers' WTPP is sustainable. Consumers with low WTPP for enterprise brand labels and consumers with high WTPP for regional brand labels have stronger willingness to repurchase.
Practical implications
The results have direct practical implications for developing brand agriculture and encouraging “brand consumption”. The results can provide theoretical reference for policymakers, enlightenment for the development and effective dissemination of agricultural brand labels and important information to e-retailers on how to sale agricultural products with agricultural brand labels.
Originality/value
To the best of the authors' knowledge, no previous study has related WTPP and its sustainability for agricultural brand labels in China. We try to fill a gap in literature on consumers' WTPP for agricultural brand labels. And the authors explore the sustainability of WTPP by analyzing the impact of WTPP on repurchase intention and recommendation intention respectively.
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The purpose of this paper was to assess and determine the impact of the five core technologies of Industry 4.0 (3D Printing, Big Data Analytics, Cloud Computing, Internet of…
Abstract
Purpose
The purpose of this paper was to assess and determine the impact of the five core technologies of Industry 4.0 (3D Printing, Big Data Analytics, Cloud Computing, Internet of Things (IoT) and Robotics) on the organizational performance of the retail industry in the context of Pakistan.
Design/methodology/approach
Pakistan's retail industry was chosen as the target sector, and the target population was composed of senior-level employees, including managers from first-level positions to top-level positions, as well as subordinate employees working under the supervision of first-level managers, possessing the technological know-how of Industry 4.0. The data were collected through a matrix-based survey questionnaire that was based on a five-point Likert scale, ranging from “strongly agree” to “strongly disagree.” The process of data analysis was conducted using IBM SPSS Statistics.
Findings
The findings obtained by this research work showed a significant relationship among the five core pillars of Industry 4.0 and the organizational performance of Pakistan's retail industry. Besides, the obtained findings provided preliminary evidence that Industry 4.0's disruptive technologies, particularly, 3D printing, big data analytics, cloud computing, IoT and robotics, could help Pakistan's retail industry solve various problems and challenges, such as meager revenues, increased expenses and unorganized systems.
Originality/value
The present study extended the theoretical body of knowledge through studying and examining Industry 4.0's five crucial factors that significantly contribute to the service sector, particularly, the retail industry, of the big emerging markets (BEM) economies, including Pakistan.
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Jamila Alieva and Daryl John Powell
The purpose of this study is to investigate the perceived effects between soft management practices, employee behaviours and the implementation of digital technologies in…
Abstract
Purpose
The purpose of this study is to investigate the perceived effects between soft management practices, employee behaviours and the implementation of digital technologies in manufacturing plants, as well as how these relate to the emergence of digital waste.
Design/methodology/approach
This paper uses case-based research. Data was collected in two large manufacturing companies based in Norway and Sweden through semi-structured interviews with two management representatives and four shop-floor employees. The data was used to evaluate 29 variables describing lean- and total quality management (TQM)-associated employee behaviours and soft management practices, in light of digital transformation.
Findings
The results suggest that several variables were positively influenced by the digital transformation process. These were top management leadership, middle management involvement, employee education, corporate social responsibility focus, innovation, knowledge sharing, work-family balance, psychological capital, job satisfaction and career commitment. Training employees, creativity, discretionary effort, turnover intention and proactivity appear to be negatively influenced by digital transformation The findings also indicate that several soft management practices and employee behaviours were not only influenced by manufacturing digitalization but also themselves influenced the process. The potential for digital waste creation was also detected in several variables, including reward and recognition and training employees.
Practical implications
Managers, practitioners and academics may learn about the importance of certain managerial practices and employees’ behavioural needs during the digital transformation process. The findings may help in prioritizing TQM and soft lean management practices and certain employee behaviours during the digital transformation and in creating awareness of digital waste.
Originality/value
This study builds on several existing studies discussing the impact of digital transformation on soft management practices and employee behaviours. It provides insights from a lean and TQM angle and offers a means of prioritizing certain practices and behaviours during a digital transformation. This study also highlights the significance of digital waste.
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