E-commerce is increasingly competitive and there is a constant need for new approaches and technology to facilitate exchange. Emerging techniques include the use of artificial intelligence (AI). One AI tool that has sparked interest in e-commerce is the automated negotiation agent (negotiation-agent). This study examines such agents, and proposes an offer strategy model of integrative negotiation for a negotiation-agent with a focus on negotiation agent-to-human interaction. More specifically, a new offer strategy was developed based on the integrative bargaining model, which emphasizes the importance of exchanging information among negotiators and multi-issue negotiation that includes package offers to achieve an integrative (win-win) outcome. This study incorporated an argumentation-based negotiation and the negotiation tactic of multiple equivalent simultaneous offers, which was programmed into the negotiation-agent. An experiment was conducted performing 49 negotiation-agent-to-human negotiations over three issues in online purchase tasks to demonstrate the effectiveness of the proposed strategy. Experimental results indicated that the proposed offer strategy with agent negotiation can enhance the persuasiveness of an offer and the performance of negotiation outcome (human counterpart's perception toward negotiation process, opponent-agent and desire for future negotiation). The findings confirmed the effectiveness of the proposed design and demonstrated an innovative approach to e-commerce transactions.

PurposeThis study aims to provide an in-depth understanding of big data analytics (BDA) in human resource management (HRM). The emergence of digital technology and the availability of large volume, high velocity and a great variety of data has forced the HRM to adopt the BDA in managing the workforce.Design/methodology/approachThis paper evaluates the past, present and future trends of HRM through the bibliometric analysis of citation, co-citation and co-word analysis.FindingsFindings from the analysis present significant research clusters that imply the knowledge structure and mapping of research streams in HRM. Challenges in BDA application and firm performances appear in all three bibliometric analyses, indicating this subject’s past, current and future trends in HRM.Practical implicationsImplications on the HRM landscape include fostering a data-driven culture in the workplace to reap the potential benefits of BDA. Firms must strategically adapt BDA as a change management initiative to transform the traditional way of managing the workforce toward adapting BDA as analytical tool in HRM decision-making.Originality/valueThis study presents past, present and future trends in BDA knowledge structure in human resources management.

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With Malaysia's rapid urbanisation and continuous improvement of living standards, vehicle ownership and trip volume continue to grow. Increases in motor traffic in large cities and their environs result in a number of social, environmental, and economic issues, which are frequently attributable to the widespread use of automobiles as the primary mode of urban transportation. This exacerbates traffic congestion on the country's highways, particularly in urban areas such as Kuala Lumpur. This traffic congestion poses an ongoing threat to the sustainability of transport development. Thus, by using the system dynamics, this study establishes a cause-and-effect relationship regarding the implementation of road pricing as a tool for reducing congestion and a stepping stone for enhancing sustainability. Road pricing is a direct charge assessed to drivers who use the road network with the goal of reducing the number of private vehicles on the road during peak hours. The developed Causal Loop Diagram (CLD) composed of five subsystems: road congestion, road attractiveness, new road construction, public transportation, and road pricing. The road congestion, new road construction, and road pricing all encounter mutual reinforcement as a result of a variety of negative polarities. As a result, authorities should place a greater emphasis on these loopholes, as they will inevitably result in unexpected changes. Additionally, by incorporating holistic perspectives from previous works and experts in the field, CLD can aid in identifying the primary factors underlying the problem being studied. In future work, the developed CLD should be extended to the next stage of the SD model, dubbed stock-flow-diagram (SFD).

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