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A cross-domain intelligent software-defined network (SDN) routing method based on a proposed multiagent deep reinforcement learning (MDRL) method is developed.

First, the network is divided into multiple subdomains managed by multiple local controllers, and the state information of each subdomain is flexibly obtained by the designed SDN multithreaded network measurement mechanism. Then, a cooperative communication module is designed to realize message transmission and message synchronization between the root and local controllers, and socket technology is used to ensure the reliability and stability of message transmission between multiple controllers to acquire global network state information in real time. Finally, after the optimal intradomain and interdomain routing paths are adaptively generated by the agents in the root and local controllers, a network traffic state prediction mechanism is designed to improve awareness of the cross-domain intelligent routing method and enable the generation of the optimal routing paths in the global network in real time.

Experimental results show that the proposed cross-domain intelligent routing method can significantly improve the network throughput and reduce the network delay and packet loss rate compared to those of the Dijkstra and open shortest path first (OSPF) routing methods.

Message transmission and message synchronization for multicontroller interdomain routing in SDN have long adaptation times and slow convergence speeds, coupled with the shortcomings of traditional interdomain routing methods, such as cumbersome configuration and inflexible acquisition of network state information. These drawbacks make it difficult to obtain global state information about the network, and the optimal routing decision cannot be made in real time, affecting network performance. This paper proposes a cross-domain intelligent SDN routing method based on a proposed MDRL method. First, the network is divided into multiple subdomains managed by multiple local controllers, and the state information of each subdomain is flexibly obtained by the designed SDN multithreaded network measurement mechanism. Then, a cooperative communication module is designed to realize message transmission and message synchronization between root and local controllers, and socket technology is used to ensure the reliability and stability of message transmission between multiple controllers to realize the real-time acquisition of global network state information. Finally, after the optimal intradomain and interdomain routing paths are adaptively generated by the agents in the root and local controllers, a prediction mechanism for the network traffic state is designed to improve awareness of the cross-domain intelligent routing method and enable the generation of the optimal routing paths in the global network in real time. Experimental results show that the proposed cross-domain intelligent routing method can significantly improve the network throughput and reduce the network delay and packet loss rate compared to those of the Dijkstra and OSPF routing methods.

The organization of services can affect the adoption of sustainable practices within the relationship between a buyer (e.g. a shipper) and a supplier (e.g. a logistics service provider–LSP). The purpose of this paper is to analyse, within this relationship, the mechanisms affecting collaboration between shippers and LSPs towards adopting green logistics practices to reduce the negative environmental effects of logistics processes. The authors take the perspective of small and medium enterprises (SMEs), which represent – although less investigated than large enterprises – a relevant field of investigation given their impact on the environmental sustainability of logistics processes.

The authors conducted a multiple case-study investigation on a set of dyads involving shippers and LSPs. The authors explored the antecedents shaping the approach to sustainability in logistics and, adopting the absorptive capacity (AC) theory, the learning and knowledge transfer processes leading to the adoption of green practices.

Collaboration between shippers and LSPs for better sustainability in logistics seems not to work when relationships are limited to simple annual (or pluriannual) contracts, and when shippers do not show ambition to improve the level of sustainability of their logistics processes (regardless of whether they show an interest in general sustainability matters). On the other hand, successful cases show higher commitment in the dyadic relationship with respect to improving logistics sustainability, good levels of communication and a more structured process of knowledge sharing, enabled by IT integration, shared performance monitoring, and creation of inter-organizational teams.

While most of the existing research focuses on the perspective of shippers or LSPs, this work is original since it explores collaborative mechanisms within a buyer-supplier relationship simultaneously taking the perspective of both parties, according to the lens of the AC. It identifies directions for improving collaboration within the shipper-LSP relationship in the context of SMEs to foster the adoption of collaborative green logistics practices to impact sustainability positively.

This study aims to investigate how organizations from different sectors interpret the meaning of business continuity management (BCM) in the light of the COVID-19 pandemic.

A survey was conducted to capture the views of organizations across five different sectors. The sample consisted of ten senior managers; two from the banking sector; two from the supply chain sector (agricultural and food supply chains); two from the tourism sector; two from the services sector; and two from the higher education sector. An interviewer-administered questionnaire was used to collect the data. One manager from each sector represented a local business/enterprise and the other represented an international business/enterprise.

It was found that different organizations/businesses understood BCM differently. Therefore, a variety of interpretations have been obtained.

This study sheds light on how different organizations understand BCM in times of crisis, such as the COVID-19 pandemic. By understanding the different interpretations, it becomes clearer whether or not these organizations have applicable business continuity plans in place.

This is the first study to investigate the different interpretations of the meaning of BCM across different business sectors. The majority of the existing studies on BCM discuss the process from the perspective of a single business or sector. The study was conducted during the COVID-19 pandemic, a period that witnessed prolonged and critical disruptions facing almost all businesses and organizations and which threatened the survival of some of them.

Focusing on the social influence processes in the context of massively multiplayer online role-playing games (MMORPGs), this study aims to investigate the nomological network of social influence factors, a topic seldom explicitly articulated in the literature in this unique context.

This study adopts a mixed-methods approach to develop and test a context-specific model of social influence processes in MMORPGs. First, the authors conducted qualitative interviews with MMORPG players to identify the drivers shaping players' perceptions of social influences. Second, the authors formulated and tested a research model with quantitative data collected from 450 respondents of an online survey.

Through the qualitative study, the authors identify leader enthusiasm, social support and social presence as the critical drivers of social influence factors. The result of the quantitative study validates the influences of the critical drivers and demonstrates the impact of social influences on MMORPG players' we-intention to continue playing games.

This research extends the social influence theory by identifying contextualized drivers that shape MMORPG players' perception of social influences determining their we-intention to continue playing games. MMORPG service providers can draw on these drivers to leverage social influences to increase players' we-intention of continuance.

In China, engineering insurance has been questioned as not being beneficial as expected. This paper seeks to further understand how China's engineering insurance industry functions and to provide a macro perspective explanation for engineering insurance's underdevelopment.

Three industrial organization hypotheses were extended to the engineering insurance context: structure conduct performance (SCP), relative market power (RMP) and efficiency structure (ES) hypotheses. This paper employed the Generalized Method of Moments (GMM) and Data Envelopment Analysis (DEA) bootstrap to test the hypotheses using panel data from 2008 to 2017.

The results suggest that the SCP paradigm is validated in China's engineering insurance market, indicating a concentrated market where the welfare of consumers (e.g. owners, contractors and designers) may be eroded. Several factors are identified to have significant impacts on engineering insurers' performance, such as the investment return, percentage of engineering business, the ratio of outstanding claims, the number of large contractors, market rivalry and entry barriers.

Despite the sheer size of China's construction industry and the urgent need to improve risk management, the insurance industry that serves construction firms engineering insurance is underdeveloped. Engineering insurance is yet to be understood from a macro perspective, which may reveal the underlying reasons for engineering insurance's underdevelopment. The industrial organization theories provided a theoretical framework to test the functioning of this specific industry. The disaggregated data (engineering line specific) is employed to ensure effective regulation and policymaking.

The COVID-19 pandemic started a new era in understanding the topic of resilience and adaptability. The human society has not faced such a widespread global challenge until now. This paper aims to address a context change influenced by the COVID-19 pandemic, using a case study in high education. While the character of the issues emerging is the same as in any other domain, in high education, the principles and consequences can be more directly studied and analyzed.

This paper describes a framework to evaluate how the context of the tertiary education service has been disrupted and the influence on the adherence of the students to the educational process, via primary quantitative data collection. This paper tackles the problem of distinguishing the change in context and context change and the possibility of system reconfiguration.

To properly face the evolving conditions induced by the pandemic, the education service system must be aligned to the imposed emergency situations, trying to “find” where the changes have emerged, i.e. what kind of reconfiguration is, whether it appears in the goals or in the service system itself. Furthermore, this study discusses how the findings can be valuable and applied to situations beyond the pandemic, in other cases of context disruption to highlight how general the service activities are within our reconfiguration approach.

From a theoretical point of view, this work is in line with main assumptions of system thinking, by confirming several insights of service systems’ behavior, even in a logic of B2B interactions (from the offer side); first in terms of openness and adaptation, in addition to readiness to change and – when and how – this change can occur. From a practical point of view, this paper’s contribution is directed toward achieving the more successful change management process, as reached together by motivated partners working hard for a common final goal. Realizing that the pandemic has brought a completely new context of education, managers should focus now on monitoring all aspects of the education business, not only directly affected projects and processes.

The paper aims to examine the state of electronic service delivery in Bangladesh. It reviews the structure and operation of the “e-service” centers at the district, sub-district (upazila), and union levels by taking an inventory and assessing their contributions.

The paper is based on a review of the functions and operations of the service delivery agencies with reference to the claims made by the government. It is based on secondary materials obtained from academic studies, government documents, relevant websites, and media reports.

Electronic delivery of public services in Bangladesh has not been effective as planned. There are issues regarding channels of communication, the competence of public officials, human and financial resources, and political will to support the agencies delivering public services.

The paper examines the arrangements, practices, and problems of delivery of public services in Bangladesh through e-service centers at the local levels to determine the progress and potentials of employing digital technology for addressing problems. It proposes the strategy for public service delivery by using digital technology in the country.

This editorial for the 6th World Conference on Production and Operations Management (P&OM) 2022 Special Issue delves into the transformative role of advanced artificial intelligence (AI)-driven chatbots in reshaping operations, supply chain management and logistics (OSCM). It aligns with the conference’s theme of exploring the intersection between P&OM and strategy during the Technological Revolution.

Utilizing a conceptual approach, this paper introduces the “ERI Framework,” a tool designed to evaluate the impact of AI-driven chatbots in three critical operational dimensions: efficiency (E), responsiveness (R) and intelligence (I). This framework is grounded in disruptive debottlenecking theory and real-world applications, offering a novel structure for analysis.

The conceptual analysis suggests immediate benefits of chatbots in enhancing decision-making and resource allocation, thereby alleviating operational bottlenecks. However, it sees challenges such as workforce adaptation and potential impacts on creativity and sustainability.

The paper suggests that while chatbots present opportunities for optimizing operational processes, organizations must thoughtfully address the emerging challenges to maintain productivity and foster innovation. Strategic implementation and employee training are highlighted as key factors for successful integration.

Bridging the gap between the burgeoning proliferation of chatbots and their practical implications in OSCM, this paper offers a first perspective on the role of AI chatbots in modern business environments. By providing insights into both the benefits and challenges of chatbot integration, it offers a preliminary view essential for academics and practitioners in the digital age.

Deep learning techniques are unavoidable in a variety of domains such as health care, computer vision, cyber-security and so on. These algorithms demand high data transfers but require bottlenecks in achieving the high speed and low latency synchronization while being implemented in the real hardware architectures. Though direct memory access controller (DMAC) has gained a brighter light of research for achieving bulk data transfers, existing direct memory access (DMA) systems continue to face the challenges of achieving high-speed communication. The purpose of this study is to develop an adaptive-configured DMA architecture for bulk data transfer with high throughput and less time-delayed computation.

The proposed methodology consists of a heterogeneous computing system integrated with specialized hardware and software. For the hardware, the authors propose an field programmable gate array (FPGA)-based DMAC, which transfers the data to the graphics processing unit (GPU) using PCI-Express. The workload characterization technique is designed using Python software and is implementable for the advanced risk machine Cortex architecture with a suitable communication interface. This module offloads the input streams of data to the FPGA and initiates the FPGA for the control flow of data to the GPU that can achieve efficient processing.

This paper presents an evaluation of a configurable workload-based DMA controller for collecting the data from the input devices and concurrently applying it to the GPU architecture, bypassing the hardware and software extraneous copies and bottlenecks via PCI Express. It also investigates the usage of adaptive DMA memory buffer allocation and workload characterization techniques. The proposed DMA architecture is compared with the other existing DMA architectures in which the performance of the proposed DMAC outperforms traditional DMA by achieving 96% throughput and 50% less latency synchronization.

The proposed gated recurrent unit has produced 95.6% accuracy in characterization of the workloads into heavy, medium and normal. The proposed model has outperformed the other algorithms and proves its strength for workload characterization.

Smartphone apps collect users' personal information, which triggers privacy concerns for app users. Consequently, app users restrict apps from accessing their personal information. This may impact the effectiveness of in-app advertising. However, research has not yet demonstrated what factors impact app users' decisions to use apps with restricted permissions. This study is aimed to bridge this gap.

Using a quantitative research method, the authors collected the data from 384 app users via a structured questionnaire. The data were analysed using AMOS and fuzzy-set qualitative comparative analysis (fsQCA).

The findings suggest privacy concerns and risks have a significant positive effect on app usage with restricted permissions, whilst reputation, trust and perceived benefits have significant negative impact on it. Some app-related factors, such as the number of apps installed and type of apps, also impact app usage with restricted permissions.

Based on the findings, the authors provided several implications for app stores, app developers and app marketers.

This study examines the factors that influence smartphone users' decisions to use apps with restricted permission requests. By doing this, the authors' study contributes to the consumer behaviour literature in the context of smartphone app usage. Also, by explaining the underlying mechanisms through which the principles of communication privacy management theory operate in smartphone app context, the authors' research contributes to the communication privacy management theory.