Knowledge Sharing in Project Environments

Projects have been increasingly used in the implementation of organizations' business operations. Knowledge sharing has been considered essential in project environment; therefore, the integration of knowledge management within project management becomes crucial for project success. The objective of this research is to study how knowledge sharing is integrated within the context of a project, and what is the perception of project team members about it. A case study was carried out in a company within the financial sector, focused on a project team of the entity. The results revealed that project managers, other professionals in project management, and the organization itself are very much aware of the importance of knowledge sharing. The results also emphasized that, regardless of the lack of incentives by top management, project team members consider that knowledge sharing highly contributes for a successful execution of projects.

Assessing Online Repurchase Intention in a Developing Country

This research investigates the factors that influence online repurchase intention in a developing country, focusing on Ghana. The study also investigates the unexplored effect of perceived value on user satisfaction and online repurchase intention. The survey method of data collection was employed. The author used the purposive technique of data collection to collect data from 504 online shoppers in two regions of Ghana. The data were analyzed using the partial least square – structural equation modeling. The findings of this study indicate that information quality, system quality, and service quality are vital drivers of consumer perceived value of products/services and consumer satisfaction. The results also confirm that perceived value significantly drives consumer satisfaction. Furthermore, the research findings suggest that consumer satisfaction and perceived value significantly influences online repurchase intention. This study extends the research on online repurchase intention, particularly within the context of a developing country.

Impact of Supply Chain Human Capability, Responsive Design, and Collaboration on Supply Chain Resilience

This paper adopts supply chain perspective to examine the impact of human capability in supply chain (SC) on SC resilience and business performance. Based on literature review, this paper expands understanding of factors, which contribute to SC resilience and competitive performance. The authors have operationalized elements of human capability in supply chain, SC collaboration, and SC responsive design to achieve this. Questionnaire was developed and was circulated to more than 600 organizations out of which 158 organizations responded and were useful. Hypotheses were formulated on studying the impact of these aspects on SC resilience and were tested using structural equation modelling. The study and the analysis support the hypothesis on the positive impact of supply chain human capability on SC collaboration and SC responsive design. Similarly, the hypothesis on SC collaboration and responsive design have tested positive impact on supply chain resilience which in turn has positive influence on organizations' performance that gives competitive edge.

A Hybrid Decision Support System for Holistic Evaluation of Material Alternatives

Selection of materials is pivotal for the success of engineering design applications. Their proper selection is an exhaustive task as a result of the presence of a wide range of material alternatives and performance attributes. Thus, this research proposes an integrated multi-criteria decision-making method for the sake of evaluating a set of material alternatives. The material alternatives are assessed with regards to their surface hardness, core hardness, surface fatigue limit, bending fatigue limit, ultimate tensile strength, and cost. The weights of attributes are obtained based on criteria importance through inter-criteria correlation (CRITIC) algorithm. This research then employs six types of multi-criteria decision-making algorithms to rank the material alternatives. Average ranking algorithm is then applied to generate a full consensus prioritization of material alternatives. A sensitivity analysis is also carried out to determine the most robust and sensitive multi-criteria decision-making algorithm.

Soft Skill-Based Training Model for Employee Retention

This study aims to assess the role and importance of Soft skills-based training in the hotels of Delhi NCR (national capital region). Such skill sets are required to motivate the employees so that they can work effectively and efficiently. The study signifies that such essential skills (e.g., team management skills, problem solving and conflict resolution, technical skills, communication and presentation skills, self-discipline, computer skills) are not only important for the personnel associated with hospitality industry but at the same time such skills helps in employee retention also. Data was collected through a questionnaire on Likert scale of 5 during a period of 9 weeks between October and November 2019. The findings suggested that employee retention which is a major issue in hospitality industry can be tackled when the service employees through proper training are coupled with the above-mentioned skillsets. This in turn can contribute significantly towards increased guest satisfaction, retention of both guests and employees and hence leading to increased revenue generation.

Information Visualization Using Clustering and Predictive Model

This paper aims to reveal the impact of rainfall on tea export from India, an issue that remained unexplored in the existing literature. This study explores a new model to predict India's tea export more accurately that would be helpful for Indian tea planters and exporters to plan their production as well as the inventory holding for deriving maximum value from tea export. A two-stage modelling approach has been developed. Firstly, an artificial intelligence-based growing hierarchical self-organising map algorithm is employed on the monthly time series of monthly frequency spreading over April 2005 to December 2013 to segregate India's monthly tea export data series into visual clusters of recognized pattern. Further, a predictive model using support vector machine has been developed and applied to forecast the tea export and then the importance of the predictor variables of the tea export have been identified. Finally, using the appropriate measures of performance a comparative analysis has been performed for each of the model. The newness of the study pertains to the two facts revealed from the study: firstly, India's tea export is embedded of complexity and nonlinearity, which could receive a successful clustering through growing hierarchical self organizing map that would make a deeper analysis easier with a further application of rich statistical techniques. Secondly, the analysis of prediction errors and the relative importance of the predictor variables establish rainfall as one of the most significant variable in predicting India's tea export, insight that has never surfaced in the literature developed thus far.

Dynamic Capabilities and New Product Development Performance

The paper aims to propose a structured multi-dimensional framework linking higher organisational capabilities such as dynamic capabilities (DC) and new product development (NPD) performance as a means by which the sustainable competitive advantage can be realised. The study lends support to supply chains that enable the firms to generate an economic surplus into the future. For this purpose, this study examines the complex inter-relationships between DC and performance in NPD using a multiple-criteria decision analysis (MCDA) approach using automotive industry data. The components of the DC model including the three capacities of sensing, seizing, and reconfiguration have been operationalised in cases featuring extensive supplier involvement in NPD projects. The findings of the study highlight that superior NPD performance including effectiveness, efficiency, and product content can be explained well by identifying and evaluating the effects of the organizational and managerial processes underlying the micro-foundations of DC.

Radio-Frequency Identification Adoption Trends in Retail

In this exploratory study, the authors conducted a Delphi study consisting of 74 experts from different sectors such as consulting, academia, retail, and third-party service providers. Expert perceptions about radio-frequency identification (RFID) adoption trends in retail including adoption status, business value dimensions, popular technology choices, and diffusion strategy are presented. The objective is to develop better RFID adoption models and strategies for making informed RFID adoption decisions.

Performance Assessment of R&D-Intensive Manufacturing Companies on Dynamic Capabilities

In today's business landscape, improving competitive advantage of manufacturing companies depends on their continuous performance improvement. This necessitates a generic and multi-dimensional view that organisational and managerial processes should be assessed by the underlying micro-foundation of dynamic capabilities (DC) in conjunction with enhanced new product development (NPD) projects. This study aims to propose an operationalised model of the conceptual DC framework including sensing, seizing, and reconfiguration capacities. The advantage of the two aforementioned models, which are based on a multi-criteria decision analysis (MCDA) framework, is that they can assist managers in the automotive industry to identify improvement plans and goals for sound and robust decision making. For this purpose, the evidential reasoning (ER) approach, which is realised in the intelligent decision system (IDS) software tool, is employed to perform performance self-assessment for the selected manufacturing companies on DC. This study provides managers with a useful tool to assess their company's strengths and weaknesses in regard to the DC components.

Multicriteria Model to Support Governance in Electoral Institutions

In democracies, power is exercised through political representation and is expressed in periodic elections. In recent decades, the population's heightened commitment to morality and the way public policies have been conducted have provoked demands from society for stricter controls and transparency in the actions of electoral institutions worldwide. In this context, considering the relevance of the performance of these institutions for legitimacy in elections and political stability, this study presents a process to support governance and election legitimacy management. The constructivist multicriteria methodology guided the construction of the model by identifying strategic objectives and highlighting properties associated with critical factors, which allowed for the measurement of performance and the identification of competitive differentials and vulnerabilities. The process of support for governance has the potential to boost performance, increase the credibility of electoral institutions, and increase society's confidence in elections.