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In light of the current challenges in the business environment, firms, particularly those involved in supply chains, must foster innovation. In this context, the current study employs the theory of dynamic organizational capabilities (DOCs) to track supply chain learning capabilities (SCLCs) and independently uncover their relationship to innovation at both the product and process levels. Similarly, the study intends to investigate the influence of technological turbulence (TT) on these relationships as a moderating variable.

The data were gathered using in-person interviews with 189 CEOs with some supply chain management proficiency from small and medium-sized enterprises (SMEs) in the industrial zones of eastern Egypt. The study used a survey approach to collect data, and the SEM-PLS technique was utilized to analyze the data.

Study findings revealed that SCLCs positively affect product and process innovation. In addition, TT positively moderates the relationship between SCLCs and product and process innovation, except for risk-taking capability. Further theoretical and practical implications are derived from the study findings.

This research adds to the knowledge of the dynamic capabilities theory (DCT), which affects how firms interact with their external environment. Studying learning capabilities are employed as essential competencies to counterbalance high levels of TT in the external environment in terms of innovative performance and vice versa if firms do not attempt to strengthen their dynamic learning capabilities in supply chains. In addition, this study contributes to the literature by studying learning capabilities from the external perspective, where SCLCs are being developed as a new variable to improve innovation.

This study explores the effect of mergers and acquisitions (M&As) on corporations' environmental, social and governance (ESG) performance and values in the Chinese financial market.

This study collected data covering 158 Chinese listed companies that have successfully completed at least one M&A activity between 2011 and 2020. Fixed effect and random models based on the Hausman test are adopted to mitigate potential heterogeneity issues in the selection.

Results show that acquiring targets with high ESG performance can help increase their own ESG performance, which in turn increases their market values. Heterogeneity and robustness tests also provide consistent results. Findings further confirm the bidirectional correlation between ESG and M&As, and then enrich related literature by suggesting the importance of utilizing M&As as a driver to increase corporate ESG performance.

This study embodies the practical implications of ESG and M&A. Managers, investors and policymakers can highly benefit from the results through practical applications.

The study aims to reveal the relative importance of each characteristic of a proactive prosumer and determine the role of each characteristic in improving technological innovation.

Our data were collected via emails using a final sample of 280 technical managers from Egypt’s information technology (IT) firms who have some software development expertise. The data were analyzed using the iterative dichotomiser 3 (ID3) algorithm.

The results indicate that proactive prosumer characteristics (initiative and creativity) positively affect technological innovation. Furthermore, there is no technological innovation without initiative.

This study uses ID3 decision tree analysis to analyze the role of proactive prosumers in technological innovation. It greatly advances the area by addressing the need for quantitative studies in administrative sciences. The study highlights initiative and creativity as essential innovation drivers, contributing to consumer and prosumption theories and the changing consumer-firm connection. The ID3 algorithm distinguishes the study from earlier statistical studies. The study’s limitations advise increasing prosumer literature, studying psychological aspects and comparing cultures. Use various algorithms and moderator and mediator factors to improve methodology. Technical managers' opinions must also be understood.

This research contributes to the existing knowledge base by examining the intricate relationship between proactive prosumers and technological innovation. It offers a novel approach by employing the ID3 decision tree algorithm within the administrative sciences, a domain that needs to be explored in prosumer research. By bridging the methodological gap, this study addresses the need for more quantitative investigations into prosumers in the management field. Furthermore, it pioneers the application of artificial intelligence techniques to analyze the prosumer phenomenon quantitatively. The paper concludes by outlining potential avenues for future research.

The purpose of this paper is to investigate masculinity in Chinese social media marketing for global luxury fashion brands through two studies.

Study 1 compares physical characteristics of males in visually oriented US (Instagram) and Chinese (Weibo) social media posts promoting global luxury fashion magazine brands (e.g. Vogue, Cosmopolitan, GQ and Esquire). Study 2 examines the prevalence of and Chinese consumers’ responses (reposts, comments and likes) to different masculinities depicted in luxury fashion brand-sponsored Weibo posts.

Male portrayals for Chinese audiences feature more characteristics associated with emerging East Asian hybrid masculinities – “Little Fresh Meat” (LFM) and “Old Grilled Meat” (OGM) – than associated with global or regional hegemonic masculinity (i.e. the scholarly Wén and action-oriented Wu). Wén remains common in social media posts for luxury fashion goods, but LFM and OGM engender more consumer responses.

Chinese luxury fashion marketing depicts masculinity more similarly to other East Asian marketing than to Western marketing. Some luxury fashion brands are struggling for acceptance among Chinese youth. Luxury fashion marketers should incorporate hybrid rather than hegemonic masculinities to prompt more favorable responses among Chinese consumers, especially younger female target markets.

Growing female occupational and consumer power and shifting male employment from blue-collar to white-collar jobs have influenced media portrayals of masculinity. Social media marketing for luxury fashion brands demonstrates the prevalence and appeal of hybrid masculinities in China.

The purpose of this paper is to examine the effect of hotel safety leadership on employee safety behavior during the COVID-19 pandemic, and the mediation role of belief restoration and the moderation role of perceived risk between safety leadership and behavior were also investigated.

The COVID-19 outbreak served as the background for a questionnaire survey of 23 hotels in China with 1,594 valid responses being received. The statistical analysis techniques used were exploratory and confirmatory factor analysis, correlation analysis, structural equation modeling and hierarchical regression.

The results showed that: hotel safety leadership positively affected employee safety behavior (compliance, participation and adaptation); belief restoration partially mediated the influence of safety leadership on safety behavior; and perceived risk negatively moderated the direct effect and the mediation effect of “safety leadership – belief restoration – safety behavior.”

The main limitation was that the questionnaires were collected with the same measurement system within a certain period of time (cross-sectional design). Then, future research should test and expand this conceptual model in different crises, business fields, theoretical orientation and cultural backgrounds.

Hotels should develop management strategies based on safety leadership and motivate and promote employee safety behavior from the four aspects of safety coaching, care, motivation and control.

This investigation expanded the research on the effectiveness of safety leadership and especially with respect to safety in the hospitality industry during a major global crisis. Also, the research conceptual model and variables contained therein are original contributions to the hospitality research literature.

The purpose of this paper is to propose an optimized hybrid model based on artificial intelligence methods, use the method of time series forecasting, to deal with the price prediction issue of China’s table grape.

The approaches follows the framework of “decomposition and ensemble,” using ensemble empirical mode decomposition (EEMD) to optimize the conventional price forecasting methods, and, integrating the multiple linear regression and support vector machine to build a hybrid model which could be applied in solving price series predicting problems.

The proposed EEMD-ADD optimized hybrid model is validated to be considered satisfactory in a case of China’ grape price forecasting in terms of its statistical measures and prediction performance.

This study would resolve the difficulties in grape price forecasting and provides an adaptive strategy for other agricultural economic predicting problems as well.

The paper fills the vacancy of concerning researches, proposes an optimized hybrid model integrating both classical econometric and artificial intelligence models to forecast price using time series method.

Tourism is a labor-intensive sector with extensive links to other industries and plays a vital role in creating employment. This study aims to propose a new framework to analyze the intrinsic structure of the employment effects of tourism-related sectors and their drivers.

This study uses input–output and structural decomposition analysis (IO-SDA) to quantify the employment effects of tourism-related sectors and their driving mechanisms based on China’s I-O tables of 2002, 2007, 2012 and 2017.

The results show a declining trend in the intensity of direct or indirect employment effects in tourism-related sectors, indicating a decreasing number of jobs directly or indirectly required to create a unit of tourism output. Among tourism-related sectors, catering has the highest intensity of indirect employment effects over the study period. Catering stimulates the indirect employment of agriculture, forestry, animal husbandry, fishery and food and tobacco manufacturing. The decomposition analysis reveals that final demand is the largest contributor to the increase in tourism employment, while technological progress shifts from an employment-creation effect in 2002–2012 to an employment-destruction effect in 2012–2017.

This study proposes a new analytical framework to investigate the structural proportional relationship between the direct and indirect employment effects of various tourism-related sectors and their dynamic changes. Doing so, it provides valuable references for policymakers to promote tourism employment.

旅游相关部门就业效应的驱动因素：以中国为例

摘要

旅游业是一个劳动密集型部门, 与其他国民经济部门有着广泛的联系, 这在创造就业方面发挥着重要作用。本研究旨在建立一个框架, 分析旅游相关部门就业效应的内在结构及其驱动因素。

本研究基于中国2002年、2007年、2012年和2017年的投入产出表, 引入投入产出和结构分解分析（IO-SDA）法量化了旅游相关行业的就业效应及其变化的驱动机制。

旅游相关部门的直接或间接就业强度呈下降趋势, 可见创造一个单位的旅游产出所需的直接或间接工作数量在减少。在旅游相关部门中, 餐饮部门在研究期内的间接就业效应强度最高, 主要带动了农、林、牧、渔业和食品及烟草制造业的间接就业。旅游就业效应变动的驱动因素中, 最终需求是旅游就业效应增加的最大贡献者, 技术效应从2002-2012年期间的就业创造效应转变为2012-2017年期间的就业破坏效应。

本研究建立了一个全新的分析框架, 可以揭示各个旅游相关部门的直接和间接就业效应之间的结构比例关系及其动态变化。对旅游就业效应的驱动因素分析可以为政策制定者提供针对性的建议, 以促进旅游就业。

Factores que impulsan los efectos del empleo en los sectores relacionados con el turismo: El caso de China continental

Resumen

El turismo es un sector intensivo en mano de obra con amplios vínculos con otras industrias y desempeña un papel vital en la creación de empleo. Este estudio propone un nuevo marco para analizar la estructura intrínseca de los efectos en el empleo de los sectores relacionados con el turismo y sus impulsores.

Este estudio utiliza el análisis de entrada-salida (input-output) y de descomposición estructural (structural decomposition) (IO-SDA) para cuantificar los efectos sobre el empleo en los sectores relacionados con el turismo y sus mecanismos impulsores, basándose en las tablas input-output de China de 2002, 2007, 2012 y 2017.

Los resultados muestran una tendencia a la baja en la intensidad de los efectos directos o indirectos del empleo en los sectores relacionados con el turismo, lo que indica un número cada vez menor de puestos de trabajo directos o indirectos necesarios para crear una unidad de producción turística. Entre los sectores relacionados con el turismo, la restauración tiene la mayor intensidad de efectos indirectos sobre el empleo durante el periodo de estudio. La restauración estimula el empleo indirecto de la agricultura, la silvicultura, la ganadería, la pesca y la fabricación de alimentos y tabaco. El análisis de descomposición revela que la demanda final es la que más contribuye al aumento del empleo turístico, mientras que el progreso tecnológico pasa de ser un efecto de creación de empleo en 2002-2012 a un efecto de destrucción de empleo en 2012-2017.

Este estudio propone un nuevo marco analítico para investigar la relación estructural proporcional entre los efectos directos e indirectos del empleo de varios sectores relacionados con el turismo y sus cambios dinámicos. De este modo, proporciona valiosas referencias para que los responsables políticos promuevan el empleo en el sector turístico.

With the arrival of the big data era, governments have appointed a chief data officer (CDO) to meet the opportunities and challenges brought by big data. The existing research on the CDOs is very limited, and what does exist focuses primarily on what are CDOs do. Little research has explored how CDOs do. To fill this gap, this study employed ambidexterity theory to investigate the ambidexterity of CDOs’ impact on data-driven innovation.

To empirically test the model, a survey study was conducted to empirically test the model. Data were collected from 261 CDOs in government and government employees in big data management centers or bureaus. The collected data were analyzed quantitatively to answer hypotheses using a structural equation model.

The findings suggest that data exploitation and data exploration significantly influence data-driven leadership, culture and value propositions. Data-driven leadership and value propositions significantly impact government performance.

This study is one of the first attempts to investigate how CDOs work, especially when promoting data-driven innovation. In addition, this study extends ambidexterity theory into the issue of the CDO in government.

This paper aims to investigate the fast attitude coordinated control problem for rigid satellite swarms with communication delays.

Based on behavior‐based control approach, the attitude control system is designed to guarantee that the attitude of the satellite swarm converge to a dynamic reference state in finite time. A fast sliding mode is developed to improve the convergence rate and robustness of the control system. All the effects of communication delays, parameter uncertainties and external disturbances are taken into account simultaneously, and the communication topology of the satellite swarm can be arbitrary types. Numerical simulations are provided to demonstrate the analytic results.

Despite the existence of communication delays, parameter uncertainties and external disturbances, the stability of the closed‐loop system can be successfully guaranteed and the proposed control strategies are effective to overcome these unexpected phenomena subject to arbitrary communication topology.

This paper introduces a fast terminal sliding mode control method which can guarantee the fast convergence of the attitude state of the satellite swarm in the presence of communication delays, switched communication topology, parameter uncertainties and external disturbances.

The purpose of this paper is to provide reference for researchers by reviewing the research advances and trend of agricultural product price forecasting methods in recent years.

This paper reviews the main research methods and their application of forecasting of agricultural product prices, summarizes the application examples of common forecasting methods, and prospects the future research directions.

1) It is the trend to use hybrid models to predict agricultural products prices in the future research; 2) the application of the prediction model based on price influencing factors should be further expanded in the future research; 3) the performance of the model should be evaluated based on DS rather than just error-based metrics in the future research; 4) seasonal adjustment models can be applied to the difficult seasonal forecasting tasks in the agriculture product prices in the future research; 5) hybrid optimization algorithm can be used to improve the prediction performance of the model in the future research.

The methods from this paper can provide reference for researchers, and the research trends proposed at the end of this paper can provide solutions or new research directions for relevant researchers.