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Industry 4.0 (I40) is an open window of opportunity for Turkey, a developed country, to eliminate technological dependence and produce with maximum productivity. However, I40, which corresponds to the fourth wave of industrial revolutions, brings both opportunities and challenges. In this context, this study aims to reveal the foresight of managers in the Turkish white goods industry (TWGI) regarding the advantages and challenges of I40 and compare them with the literature.

The Delphi method was used for the study. Data were collected from managers of companies that are members of the White Goods Suppliers Association (BEYSAD). Seventy managers from 55 companies participated in the first round, and 19 managers participated in the second round of Delphi.

The results show that the most frequently cited advantages are productivity/resource efficiency, data and information-enabled effectiveness/productivity, quality 4.0 and competitiveness/strategy. The most frequently mentioned challenges are financial resources/investment, employee qualification/training, technical/processual challenges and organizational transformation/leadership.

The sample was limited to the managers of the TWGI.

Players in similar ecosystems and policymakers should consider the advantages and respond to potential challenges when creating roadmaps, taking the necessary steps and positioning themselves in the marketplace. In particular, the TWGI – Turkey’s showcase in international markets – should consider the undeniable benefits of the I40 transition to increase innovation.

The findings for the first time highlight the advantages and challenges of I40 in an industry in Turkey, and they will benefit the TWGI, which is among the leaders in Turkey in terms of digital maturity and innovation in its journey to I40.

This paper delves into cross-border E-business, unraveling its intricate dynamics and forecasting its future trajectory.

This paper projects the prospective market size of cross-border E-business in China for the year 2023 using the GM (1,1) gray forecasting model. Furthermore, to enhance the analysis, the paper attempts to simulate and forecast the size of China’s cross-border E-business sector using the GM (1,3) gray model. This extended model considers not only the historical trends of cross-border E-business but also the growth patterns of GDP and the digital economy.

The forecast indicates a market size of 18,760 to 18,934 billion RMB in 2023, aligning with the consistent growth observed in previous years. This suggests a sustained positive trajectory for cross-border E-business.

Cross-border e-commerce critically shapes China’s global integration and traditional industry development. The research in this paper provides insights beyond statistical trends, contributing to a nuanced understanding of the pivotal role played by cross-border e-commerce in shaping China’s economic future.

The purpose of this paper is twofold: to identify and map contemporary research on advanced technology implementations for problem-solving purposes in the manufacturing industry, and to further understand the organizational learning possibilities of advanced technology problem-solving in the manufacturing industry.

This paper outlines a scoping review of contemporary research on the subject. The findings of the review are discussed in the light of theories of contradicting learning logics.

This paper shows that contemporary research on the subject is characterized by technological determinism and strong solution-focus. A discussion on the manufacturing industries’ contextual reasons for this in relation to contradicting learning logics shows that a Mode-2 problem-solving approach could facilitate further learning and expand knowledge on advanced technology problem-solving in the manufacturing industry. A research agenda with six propositions is provided.

The introduction of advanced technology implies complex effects on the manufacturing industry in general, while previous research shows a clear focus on technological aspects of this transformation. This paper provides value by providing novel knowledge on the relationship between advanced technology, problem-solving and organizational learning in the manufacturing industry.