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1 – 10 of 30Shanzhong Du and June Cao
Industrial robots are of great significance to the long-term development of family firms. Drawing on the lens of the principal–principal conflict, this paper aims to investigate…
Abstract
Purpose
Industrial robots are of great significance to the long-term development of family firms. Drawing on the lens of the principal–principal conflict, this paper aims to investigate the influence of family non-executive directors on robot adoption in Chinese family firms.
Design/methodology/approach
This paper selects the family firms in China from 2011 to 2019 as the sample. Furthermore, the authors manually collected the family non-executive directors and constructed the robot adoption variable utilizing data sourced from the International Federation of Robotics. In brief, this paper constructs a comprehensive framework of the mechanisms and additional tests pertaining to the influence of family non-executive directors on robot adoption.
Findings
This paper finds that family non-executive directors can promote robot adoption in family firms. The underlying mechanism analysis shows that family non-executive directors promote robot adoption by exerting financial and human effects. This paper further finds that the characteristics of family non-executive directors, such as kinship, differential shareholding and excessive directors, affect the role of family non-executive directors. Finally, robot adoption can improve future performance, and the promotional effect is more evident when family members are non-executive directors.
Originality/value
This paper contributes to the related literature from the following two aspects. Firstly, this paper decomposes the types of family directors to understand the role of family non-executive directors, which challenges the assumption that family board members are homogeneous in family firms. Second, this paper expands the research on the factors that influence robot adoption in emerging economies from the micro-enterprise level. In addition, the findings in this paper have managerial implications for family firms to optimize their strategic decisions with the help of the mode of board right allocation.
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The purpose of this paper is to examine the hotel growth model including hotel brand, culture and life cycle phases of the Myrtle Beach, South Carolina, the fastest growing…
Abstract
Purpose
The purpose of this paper is to examine the hotel growth model including hotel brand, culture and life cycle phases of the Myrtle Beach, South Carolina, the fastest growing tourism destination in the United States.
Design/methodology/approach
Culture reflecting consuming behaviour of low-context innovators and high-context imitators is measured by the price elasticity of demand (PED). Hotel brand reflecting guests’ hotel class is measured by the income elasticity of demand. Autoregressive distributed lag has been conducted on the Smith Travel Research data in 33 years (1989–2022) to determine the relationship among hotel brand, culture and life cycles.
Findings
Skilled labour is the key to make hotels grow. Therefore, increase room rates when hotels possess skilled professionals and decrease room rates when hotels have no skilled professionals. During the rejuvenation in Myrtle Beach (1999–2003), hoteliers increased room rates for innovators due to skilled professionals to increase revenue. Otherwise, a decrease in room rates due to lack of skilled professionals would lead to increase revenue.
Research limitations/implications
(1) Although Myrtle Beach is one of the fastest growing tourism destinations in the US, it has a relatively small geographic area relative to the country. (2) Data cover over one tourist life cycle, so the time span is relatively short. Hoteliers can forecast the number of guests in different culture by changing room rates.
Practical implications
To optimize revenue, hoteliers can select skilled labour in professional design hotel brands which could make an increase in demand for leisure transient guests no matter what room rates increase after COVID-19 pandemic.
Social implications
The study has considered the applied ethical processes regarding revenue management that would maximize both revenue and customer satisfaction when it set up an increase in room rates to compensate for professional hotel room design or it decreases room rates for low-income imitators in exploration and development.
Originality/value
This research highlights that (1) skilled design in the luxury hotel brand is the key for the hotel growth and (2) there is a steady state of the growth model in the destination life cycle.
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Muhammad Muzummil Sibtain, Muhammad Hashim, Fausto Pedro García Márquez, Sajjad Ahmad Baig and Muhammad Nazam
The adoption of energy-efficient systems is crucial for Pakistan to meet its growing energy demand and address its energy challenges. However, adoption of these systems in…
Abstract
Purpose
The adoption of energy-efficient systems is crucial for Pakistan to meet its growing energy demand and address its energy challenges. However, adoption of these systems in Pakistan is hindered by several barriers, including economic constraints, lack of awareness and social attitudes toward sustainable development. Therefore, the purpose of this study is to explore adoption of energy-efficient household systems and the associated social influence.
Design/methodology/approach
The study incorporates social influence as a mediating factor to examine the relationships between awareness of consequences, perceived consumer effectiveness and attitudes toward the adoption of energy-efficient systems. A quantitative survey method was used to collect data from households from Faisalabad, Pakistan. A total of 203 valid questionnaires were received and data analyzed through SmartPLS 4 for structural equation modeling.
Findings
The results revealed that awareness of consequences positively impacts compliance, social identification and internalization, while perceived consumer effectiveness has a positive relationship with social identification and internalization. Moreover, the positive association of social identification and internalization with attitude were supported but relationship of compliance with attitude was unsupported.
Practical implications
The results may also be used to develop compelling marketing campaigns focusing environmental conservation and social influence for positive attitude development.
Originality/value
The study contributes to theoretical literature by examining the empirical relationships between specific individual characteristics and societal pressure that play a critical role in shaping attitudes toward the acceptance of energy-efficient systems. Additionally, the study's findings offer actionable implications for policymakers and marketers, contributing to the development of targeted interventions for promoting sustainable consumption.
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Luan Thanh Le and Trang Xuan-Thi-Thu
To achieve the Sustainable Development Goals (SDGs) in the era of Logistics 4.0, machine learning (ML) techniques and simulations have emerged as highly optimized tools. This…
Abstract
Purpose
To achieve the Sustainable Development Goals (SDGs) in the era of Logistics 4.0, machine learning (ML) techniques and simulations have emerged as highly optimized tools. This study examines the operational dynamics of a supply chain (SC) in Vietnam as a case study utilizing an ML simulation approach.
Design/methodology/approach
A robust fuel consumption estimation model is constructed by leveraging multiple linear regression (MLR) and artificial neural network (ANN). Subsequently, the proposed model is seamlessly integrated into a cutting-edge SC simulation framework.
Findings
This paper provides valuable insights and actionable recommendations, empowering SC practitioners to optimize operational efficiencies and fostering an avenue for further scholarly investigations and advancements in this field.
Originality/value
This study introduces a novel approach assessing sustainable SC performance by utilizing both traditional regression and ML models to estimate transportation costs, which are then inputted into the discrete event simulation (DES) model.
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Yingqian Gu, Wenqi Zhang, Lin Sha and Lixia Wang
This paper aims to explore the impact of corporate financialization (CF) on green innovation (GI) and further disclose the moderating role of CEO’s individual characteristics in…
Abstract
Purpose
This paper aims to explore the impact of corporate financialization (CF) on green innovation (GI) and further disclose the moderating role of CEO’s individual characteristics in such relationship from the perspective of corporate governance.
Design/methodology/approach
This paper uses empirical research methods to study the impact of CF on GI based on the evidence from China capital market.
Findings
The findings indicate that: CF has a significant inhibiting effect on GI; female CEOs weaken the inhibiting effect of CF on GI compared to male CEOs; and CEO’s financial background positively moderates the inhibiting effect of CF on GI.
Originality/value
This paper, first, supplements the research literature on the economic consequences of CF and influencing factors of GI in non-financial firms. Then, it opens up the internal impact mechanism of CF on GI, which is moderated by the individual characteristics of corporate CEOs. Finally, it provides important reference for how to suppress CF of non-financial firms, cultivate CEOs that meet the needs of corporate development and promote GI development of enterprises through empirical evidence from China.
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Solomon Oyebisi, Mahaad Issa Shammas, Hilary Owamah and Samuel Oladeji
The purpose of this study is to forecast the mechanical properties of ternary blended concrete (TBC) modified with oyster shell powder (OSP) and shea nutshell ash (SNA) using deep…
Abstract
Purpose
The purpose of this study is to forecast the mechanical properties of ternary blended concrete (TBC) modified with oyster shell powder (OSP) and shea nutshell ash (SNA) using deep neural network (DNN) models.
Design/methodology/approach
DNN models with three hidden layers, each layer containing 5–30 nodes, were used to predict the target variables (compressive strength [CS], flexural strength [FS] and split tensile strength [STS]) for the eight input variables of concrete classes 25 and 30 MPa. The concrete samples were cured for 3–120 days. Levenberg−Marquardt's backpropagation learning technique trained the networks, and the model's precision was confirmed using the experimental data set.
Findings
The DNN model with a 25-node structure yielded a strong relation for training, validating and testing the input and output variables with the lowest mean squared error (MSE) and the highest correlation coefficient (R) values of 0.0099 and 99.91% for CS and 0.010 and 98.42% for FS compared to other architectures. However, the DNN model with a 20-node architecture yielded a strong correlation for STS, with the lowest MSE and the highest R values of 0.013 and 97.26%. Strong relationships were found between the developed models and raw experimental data sets, with R2 values of 99.58%, 97.85% and 97.58% for CS, FS and STS, respectively.
Originality/value
To the best of the authors’ knowledge, this novel research establishes the prospects of replacing SNA and OSP with Portland limestone cement (PLC) to produce TBC. In addition, predicting the CS, FS and STS of TBC modified with OSP and SNA using DNN models is original, optimizing the time, cost and quality of concrete.
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This study aims to propose a force control algorithm based on neural networks, which enables a robot to follow a changing reference force trajectory when in contact with human…
Abstract
Purpose
This study aims to propose a force control algorithm based on neural networks, which enables a robot to follow a changing reference force trajectory when in contact with human skin while maintaining a stable tracking force.
Design/methodology/approach
Aiming at the challenge of robots having difficulty tracking changing force trajectories in skin contact scenarios, a single neuron algorithm adaptive proportional – integral – derivative online compensation is used based on traditional impedance control. At the same time, to better adapt to changes in the skin contact environment, a gated recurrent unit (GRU) network is used to model and predict skin elasticity coefficients, thus adjusting to the uncertainty of skin environments.
Findings
In two robot–skin interaction experiments, compared with the traditional impedance control and robot force control algorithm based on the radial basis function model and iterative algorithm, the maximum absolute force error, the average absolute force error and the standard deviation of the force error are all decreased.
Research limitations/implications
As the training process of the GRU network is currently conducted offline, the focus in the subsequent phase is to refine the network to facilitate real-time computation of the algorithm.
Practical implications
This algorithm can be applied to robot massage, robot B-ultrasound and other robot-assisted treatment scenarios.
Originality/value
As the proposed approach obtains effective force tracking during robot–skin contact and is verified by the experiment, this approach can be used in robot–skin contact scenarios to enhance the accuracy of force application by a robot.
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Heyong Wang, Long Gu and Ming Hong
This paper aims to provide a reference for the development of digital transformation from the perspective of manufacturing process links.
Abstract
Purpose
This paper aims to provide a reference for the development of digital transformation from the perspective of manufacturing process links.
Design/methodology/approach
This paper applies canonical correlation analysis based on digital technology patents in the key links of manufacturing industries (product design, procurement, product manufacturing, warehousing and transportation, and wholesale and retail) and the related indicators of economic benefits of regions in China.
Findings
(1) The degree of digitalization of manufacturing process links is significantly correlated with economic benefits. (2) The improvement of the degree of digitalization in the “product design” link, the “warehousing and transportation” link, the “product manufacturing” link and the “wholesale and retail” link has significant impacts on the economic benefits of manufacturing industry. (3) The digital degree of the “procurement” link has no obvious influence on the economic benefits of manufacturing industry.
Practical implications
The research results can provide reference for the formulation and implementation of micro policies. The strategy of improving the level of digital transformation of key links of manufacturing industry is put forward to better promote both the digital transformation of manufacturing industry and economic development.
Originality/value
This paper innovatively studies the relationship between digitalization of manufacturing process links and economic benefits. The findings can provide theoretical and empirical support for the digital transformation of China's manufacturing industry and high-quality development of economy.
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Andry Alamsyah, Fadiah Nadhila and Nabila Kalvina Izumi
Technology serves as a key catalyst in shaping society and the economy, significantly altering customer dynamics. Through a deep understanding of these evolving behaviors, a…
Abstract
Purpose
Technology serves as a key catalyst in shaping society and the economy, significantly altering customer dynamics. Through a deep understanding of these evolving behaviors, a service can be tailored to address each customer's unique needs and personality. We introduce a strategy to integrate customer complaints with their personality traits, enabling responses that resonate with the customer’s unique personality.
Design/methodology/approach
We propose a strategy to incorporate customer complaints with their personality traits, enabling responses that reflect the customer’s unique personality. Our approach is twofold: firstly, we employ the customer complaints ontology (CCOntology) framework enforced with multi-class classification based on a machine learning algorithm, to classify complaints. Secondly, we leverage the personality measurement platform (PMP), powered by the big five personality model to predict customer’s personalities. We develop the framework for the Indonesian language by extracting tweets containing customer complaints directed towards Indonesia's three biggest e-commerce services.
Findings
By mapping customer complaints and their personality type, we can identify specific personality traits associated with customer dissatisfaction. Thus, personalizing how we offer the solution based on specific characteristics.
Originality/value
The research enriches the state-of-the-art personalizing service research based on captured customer behavior. Thus, our research fills the research gap in considering customer personalities. We provide comprehensive insights by aligning customer feedback with corresponding personality traits extracted from social media data. The result is a highly customized response mechanism attuned to individual customer preferences and requirements.
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This study examines how informal business networks achieve marketing goals in socially uncertain contexts. Drawing from multiple historical sources, Shangbangs, a type of business…
Abstract
Purpose
This study examines how informal business networks achieve marketing goals in socially uncertain contexts. Drawing from multiple historical sources, Shangbangs, a type of business network that thrived in pre-1949 China, are analyzed.
Design/methodology/approach
The Critical Historical Research Method (CHRM) undergirds a study of Shangbangs’ historicity (i.e. their socio-historically embedded multiplicity, including organizational forms, activities and connotations.
Findings
As informal regional, professional, project-based, special-product-based or mixed marketing networks, Shangbangs relied on “flexible specialization” and coupled multiple business needs to market goods and services, business organizations, specific social values and, when necessary, to debrand business rivals.
Research limitations/implications
This analysis extends theories about marketing networks by probing their subtypes, diverse marketing activities, multipronged channels and relationship building with social entities (including underground societies, business associations and guilds) in response to pre-1949 China’s market uncertainties. Substantiating an alternative approach to “flexible specialization” and marketing innovations within the pre-1949 Chinese economy shows how a parallel theoretical framework can complement western-based marketing theories.
Originality/value
This first comprehensive analysis of Shangbangs, an innovative historical Chinese marketing network outside the conventional market-corporate dichotomy, can inform theory building for marketing strategy-making and management conditioned by social contexts.
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