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This study aims to analyze and discuss whether and how consumer-to-manufacturer (C2M) mode empowered by e-commerce retail platforms’ big data affects the stock returns of firms in supply chains.

This study selects 195 companies affected by four C2M events as samples and empirically analyzes the impact mechanisms of C2M mode on supply chain firms’ stock returns by event study.

This paper finds that C2M announcements own a positive impact on the stock returns of supply chain firms. Further, the results show that the business and financial characteristics play a significant impact on the relationship between the C2M mode and firm stock return performance. For example, C2M mode leads to huge stock returns when firms cooperate with the platforms related to their business content. In addition, the business scope can strengthen the positive promotion of C2M mode in stock returns, while business concentration weakens the positive promotion of C2M mode in stock returns.

The results found in this paper can provide practical guidance for the firms in supply chains to further apply C2M mode from the business characteristics and financial performance view.

To respond to customer needs and achieve customized manufacturing, the manufacturing industry, as represented by electronics assembly companies, has embarked on a path of business model transformation (customer to manufacturer [C2M]). The purpose of this paper is to examine the practical application of assembly line-Seru conversion in a Chinese electronics assembly company during the C2M transition.

To begin with, this paper proposed a production line improvement scheme suitable for the conversion of C2M manufacturing enterprise assembly line-Seru based on an analysis of the difficulties encountered in the existing production line of A company in China. Then, a mathematical model was presented for the minimum value of the makespan and the maximum workers’ expenditure between Serus. Finally, the SA-NSGA-II algorithm and the entropy-weight TOPSIS approach were used to determine the optimal scheme for Seru unit, batch, product type and worker distribution.

Seru production and multiskilled workers are more suited to the C2M business model. The most effective strategy for worker allocation can reduce the number of employees and makespan in Serus. Additionally, the performance of the SA-NSGA-II algorithm and the method of selecting the optimal solution from the Pareto solution by the entropy-weighted TOPSIS method is also demonstrated.

Through a detailed study of how to transform the production line, other companies can apply the methods outlined in this article to shorten the delivery time, make full use of the abilities of workers and assign workers to specific positions, thereby reducing the number of workers, workers’ expenditure and improving the balance rate of production lines.

Given the scarcity of studies on the production method of C2M-type firms in the prior literature, this paper examined the assembly line-Seru conversion problem with the goal of minimizing the makespan and worker expenditure. To address the NSGA-II algorithm’s insufficient convergence, the simulated annealing process is incorporated into the method, which improves the optimization performance.

In the crowd intelligence networking era, the smart connections of human, machines and things enable point-to-point trustable transactions and distributed efficient collaboration; the smart connections among government, enterprises, organizations and the public would enable active participation of the public in society management and decision-making and improve the efficiency of government management and services. All interactions among various agents can be viewed as the transaction activity. The social division of labor system drives the evolution of transaction. The transaction mode also differentiated into different patterns with the development of human society. What will be the intelligent transaction in the crowd intelligence networking era? What will be the transactions modes and rules in the crowd intelligence networking era? The answers to these questions are of great importance to the future development of transactions.

The authors review the evolution of traditional transaction and transaction modes and analyze the driving forces of it. They attempt to give the definitions of intelligent transaction and intelligent transaction mode. They also review the traditional transaction modes and rules, analyze the characteristics of the intelligent transaction and classify the intelligent transaction modes.

The authors find the intelligent transaction is mainly reflected in the intellectualization of transaction subject, transaction object and transaction process. They summarize the characteristics of intelligent transaction and develop four modes for the intelligent transactions based on the modularization level of the transaction objects and the quantity of transaction subjects, including the demand side and the supply side. The authors also show representative examples to further illustrate rules and features of these transaction modes and point out the potential research directions.

This study is among the first to analyze the characteristics of the intelligent transaction, and the proposed division framework of the intelligent transaction modes could not only add value to the future research of intelligent transaction modes and rules but also help to guide the transactions in the crowd intelligence network.

T Education is a leading educational science and technology enterprise in China with technology-driven, talent intimacy and quality leadership as the core development objectives. Since its inception, it has been committed to creating better learning experience for children. As the predecessor of T-education, X-education was founded in Beijing in 2003. At first, it mainly provided after-school math counseling for school-age children. Over the past 10 years, its business has been expanding, covering almost every aspect of school-age education. This case studies accounting issues and business ethics challenges that firms may face when they transform from a single (traditional education) line of business to a multiple channel business.

Data collecting systems are described and the faults and problems indicated. Examples are given of the effort to prepare the data for analysis. The data analysis was carried out in collaboration with the University of Bradford, including FMECA, trend analysis and distribution fitting. The results of the analysis were compared with data from the SRS databank and with subjective estimates provided by Gasunie engineers. On the basis of the experience, recommendations are given to increase efficiency of data collection systems.

Supply chains evolve and change in size, shape and configuration, and in how they are coordinated, controlled and managed. Some supply chains are mature and relatively unchanging. Some are subject to significant change. New supply chains may emerge and evolve for a variety of reasons. The purpose of this paper is to examine the nature of supply chain evolution and address the question “What makes a supply chain like it is?”

The paper analyses and develops key aspects, concepts and principal themes concerning the emergence and evolution of supply chains over their lifecycle.

The paper defines the supply chain lifecycle and identifies six factors that interact and may affect a supply chain over its lifecycle – technology and innovation, economics, markets and competition, policy and regulation, procurement and sourcing, supply chain strategies and re-engineering. A number of emergent themes and propositions on factors affecting a supply chain’s characteristics over its lifecycle are presented. The paper argues that a new science is needed to investigate and understand the supply chain lifecycle.

Supply chains are critical for the world economy and essential for modern life. Understanding the supply chain lifecycle and how supply chains evolve provides new perspectives for contemporary supply chain design and management.

The paper presents detailed analysis, critique and reflections from leading researchers on emerging, evolving and mature supply chains.

The purpose of this paper is to identify and explore potential applications of cyborgian technologies within service contexts and how service providers may leverage the integration of cyborgian service actors into their service proposition. In doing so, the paper proposes a new category of “melded” frontline employees (FLEs), where advanced technologies become embodied within human actors. The paper presents potential opportunities and challenges that may arise through cyborg technological advancements and proposes a future research agenda related to these.

This study draws on literature in the fields of services management, artificial intelligence, robotics, intelligence augmentation (IA) and human intelligence to conceptualise potential cyborgian applications.

The paper examines how cyborg bio- and psychophysical characteristics may significantly differentiate the nature of service interactions from traditional “unenhanced” service interactions. In doing so, the authors propose “melding” as a conceptual category of technological impact on FLEs. This category reflects the embodiment of emergent technologies not previously captured within existing literature on cyborgs. The authors examine how traditional roles of FLEs will be potentially impacted by the integration of emergent cyborg technologies, such as neural interfaces and implants, into service contexts before outlining future research directions related to these, specifically highlighting the range of ethical considerations.

Service interactions with cyborg FLEs represent a new context for examining the potential impact of cyborgs. This paper explores how technological advancements will alter the individual capacities of humans to enable such employees to intuitively and empathetically create solutions to complex service challenges. In doing so, the authors augment the extant literature on cyborgs, such as the body hacking movement. The paper also outlines a research agenda to address the potential consequences of cyborgian integration.

To determine how to best deploy the Triple-A supply chain (SC) capabilities (AAA-agility, adaptability and alignment) to improve competitive advantage (CA) by identifying the Triple-A SC model with the highest CA predictive capability.

Assessment of in-sample and out-of-sample predictive capacity of Triple-A-CA models (considering AAA as individual constructs) to find which has the highest CA predictive capacity. BIC, BIC-Akaike weights and PLSpredict are used in a multi-country, multi-informant, multi-sector 304 plant sample.

Greater direct relationship model (DRM) in-sample and out-of-sample CA predictive capacity suggests DRM's greater likelihood of achieving a higher CA predictive capacity than mediated relationship model (MRM). So, DRM can be considered a benchmark for research/practice and the Triple-A SC capabilities as independent levers of performance/CA.

DRM emerges as a reference for analysing how to trigger the three Triple-A SC levers for better performance/CA predictive capacity. Therefore, MRM proposals should be compared to DRM to determine whether their performance is significantly better considering the study's aim.

Results with our sample justify how managers can suitably deploy the Triple-A SC capabilities to improve CA by implementing AAA as independent levers. Single capability deployment does not require levels to be reached in others.

First research considering Triple-A SC capability deployment to better improve performance/CA focusing on model's predictive capability (essential for decision-making), further highlighting the lack of theory and contrasted models for Lee's Triple-A framework.

With more demand-driven innovation activities, manufacturers must proactively engage in information sharing activities with their customers for better innovation performance. This study aims to inquire into the impacts of information sharing activities between manufacturers and customers (including information system usage and information content sharing) on manufacturers’ innovation performance and considers interfirm justice (including distributive justice, procedural justice and interactional justice) as information sharing antecedents.

The social exchange theory is applied to develop the conceptual model. The authors examine the conceptual model with the structural equation modeling approach using data collected from 213 Chinese manufacturers.

Interactional justice promotes information system usage. Both interactional justice and procedural justice increase information content sharing, while distributive justice decreases it. Information content sharing directly improves innovation performance and fully mediates the relationship between information system usage and innovation performance.

This research enriches empirical studies on justice-information sharing relationships by systematically investigating the impacts of three types of justice on different information sharing activities. It also adds to the application of social exchange theory in the practices of interfirm justice and information sharing. Besides, it probes into influencing mechanisms of different information sharing activities, information system usage and information content sharing, on innovation performance. The findings can guide firms to implement interfirm justice and information sharing practices for superior innovation performance.

This study looks beyond firm boundaries to depict supply chain (SC) adaptability and classifies it into internal, customer and supplier dimensions to investigate their performance implications, respectively. This study also examines the enablers of SC adaptability based on information processing theory.

This study applies the structural equation modeling method to investigate relationships among SC information sharing, SC adaptability and operational performance using data collected from 216 manufacturers in China.

Internal information sharing has a positive impact on three dimensions of SC adaptability, whereas supplier and customer information sharing only have a positive impact on supplier adaptability. Customer and supplier information sharing interact to positively influence the three dimensions of SC adaptability, while internal and customer information sharing interact to negatively affect customer adaptability. We also find that all the three dimensions of SC adaptability can enhance operational performance.

This study contributes to providing a holistic definition of SC adaptability and classifies it into three dimensions. It also investigates antecedents and performance outcomes of SC adaptability.