Author:
Chakrabartty Satyendra Nath,Sinha Deepankar
Abstract
Country-wise Logistics Performance Index (LPI) is insufficient to guide changing policies for different sectors with varied logistics requirements and perspectives. Each perspective has various measures, and hence a battery of scales is mandated to measure the performance for an individual sector like marine, agriculture, and similar. For the marine-product sector of India, scores are transformed and combined to follow normal distributions enabling parametric analysis. A method of sector-specific logistics performance index (LPI-S) is proposed addressing multi-dimensional, multi-scale response categories satisfying the desired properties of an index. An empirical illustration is given to assess LPI-S for the marine-product sector in India, combining responses of 141 Indian marine exporters in a battery with nine dimensions. The proposed method generates continuous, monotonic data, and distributions of dimension/battery scores are normal. The LPI-S scores have better arithmetic aggregation admissibility, even if lengths of dimensions are different. In addition, it identifies critical dimensions, detects changes by longitudinal data, and dimension-wise elasticity reflecting the sensitivity of the dimension from snap-shot data. Irrespective of dimensions and types of data, the proposed methodology uses the sensitivity of a dimension on LPI-S to help policy makings separately for individual categories to improve logistics efficiency. The study identified eight crucial dimensions associated with marine product logistics. The sensitivity of these dimensions in the descending order of importance were - Information system, Regulatory process, Safety & Security issues, Timeliness and Completeness efficiency, Sustainability in logistics, Operating conditions, Logistics facility pricing, Quality of Logistic services, Transportation Networks and Logistics infrastructure. Such ordering of dimensions help in deciding policy priorities.
Publisher
Penerbit UMT, Universiti Malaysia Terengganu
Reference48 articles.
1. Arvis, J. F., Saslavsky, D., Ojala, L., Shepherd, B., Busch, C., Raj, A., & Naula, T. (2016). Connecting to compete: Trade logistics in the global economy. Washington DC: World Bank
2. Bastien, C. H., Vallieres, A., & Morin, C. M. (2001). Validation of the insomnia severity index as an outcome measure for insomnia research. Sleep Medicine, 2(4), 297–307.
3. Beysenbaev, R. (2018). The importance of country-level logistics efficiency assessment to the development of international trade. British Journal for Social and Economic Research, 3(6), 13–20.
4. Bound, J., Brown, Ch., & Mathiowetz, N. (2000). Measurement Error in Survey Data (Report No. 00-450). Population Studies Center at the Institute for Social Research University of Michigan
5. Bradburn, N. M., Sudman, S., & Wansink, B. (2004). Asking questions: The definitive guide to questionnaire design—for market research, political polls, and social and health questionnaires. San Francisco: Jossey-Bass