Effect of Service Quality on Customer Loyalty: the Mediation of Customer Satisfaction, and Corporate Reputation in Banking Industry
Ho Dinh Phi and Dien Pham Huong
The COVID-19 pandemic caused disruptions in global supply chains that have resulted in prolonged shortages and financial hardships for many corporations. While organizations have dealt with supply chain interruptions for natural disasters and stock market crashes before, the COVID-19 pandemic presented a larger and unique challenge, and it required the need for resiliency in supply chains. This paper discusses several alternatives that can mitigate potential supply chain disruptions. Despite the natural inclination to protect domestic companies and industries, this paper cautions against the use of protectionism policies to prevent supply chain disruptions, as protectionism is proven to be damaging to innovation and eliminates the positive aspects of international trade and globalization. The paper recommends that governments and corporations establish strategically designed and aligned public-private partnerships that simultaneously encourage the principles of the free-market economy while providing increased preparation for supply chain disruptions caused by future global events. We further attest that Public-private partnerships will increase supply chain resiliency while simultaneously enhancing public welfare.
Keywords: COVID-19 Pandemic, Supply Chains, Globalization, Protectionism, Public Policy, Public-Private Partnerships
Inventory Forecasting and Control Decisions for Effective Inventory Management in the South African Automotive Component Manufacturing Industry: Pre COVID-19 and Lockdown Period
Sandra Perks and Jason Delport
The COVID-19 global health pandemic significantly affected the global economy and the automotive industry when lockdown measures were implemented. This study seeks to investigate the influence of inventory forecasting and control decisions on effective inventory management in the South African automotive component manufacturing (SAACM) industry. Using a positivistic paradigm with a quantitative research approach, data was sourced from 162 Automotive Component Manufacturers (ACMs) to establish whether their inventory forecasting and control decisions changed from prior COVID-19 to the lockdown period during the COVID-19 pandemic. The multiple regression analysis found statistically significant relationships between inventory forecasting decisions and effective inventory management prior to COVID-19, inventory control decisions and effective inventory management prior to COVID-19 and inventory forecasting decisions and effective inventory management during the lockdown period. Thus, regardless of the COVID-19 pandemic, inventory managers in ACMs in South Africa (SA) should use inventory forecasting methods such as demand forecasting, economic order quantity and materials requirement planning. They should further consider using an inventory information sharing system and inventory replenishment procedure to manage inventory more effectively.
Keywords: COVID-19, Effective Inventory Management, Inventory Forecasting, Inventory Control, Lockdown Period, South Africa
Optimality of Buy-and-Hold Strategies
Qi Liu and Ka Po Kung
The buy-and-hold way of investing has been taken as gospel by many professional investors since the 1960s. In recent years, however, it has come under harsh attack from both academics and practitioners who claim its ineffectiveness in the face of increasingly volatile markets. This research takes a theoretical approach to evaluating its effectiveness by invoking a powerful optimality theorem to gauge its effectiveness or, more specifically, its optimality level. In terms of optimality level, we determine how well it fares against three other popular strategies – lock-in, random-timing, and stop-loss. To make the concept of optimality level practically operational, we set up a two-factor model to depict the market environment and use Monte Carlo simulation to determine the optimality levels of these strategies. In terms of average optimality level, our results show that, in general, buy-and-hold strategies outperform the other three strategies in stable market environment, but they are outperformed by lock-in and stop-loss strategies in volatile market environment.
Keywords: Buy-and-Hold, Optimality Level, Strategies, Two-Factor Model, Simulation
Grant Amount and Firm Revenue Performance: Moderating Effects of Government Financial Support Scheme
Timothy Olaniyi Aluko and Innocent Bayai
This study tests the interaction effect of government financial support for small businesses in the relationship between business revenue and the grant-approved amount in the post-financial support scheme in South Africa. Pre- and post-internal administrative datasets of the beneficiary firm were collected from the scheme between 2011 – 2018. The regression estimation procedure was based on the Pooled OLS regression and the GLS Random Effects (RE) model based on the Breusch-Pagan Lagrangian multiplier test. The theoretical approach in the study is based on the capital-revenue framework of firm output, represented by firms’ revenue performance level post-financial assistance, which serves as a marker of the beneficiary firm’s revenue performance. Findings show, grant-approved amount had a statistically significant and positive effect on the revenue growth of grant beneficiary firms. The indication is for every 1 per cent increase in grant amount received by firms led to about a one per cent increase in revenue growth. The finding has useful implications to help strengthen the provision of government grants to small enterprises and provide a new framework for future studies on small business performance looking at the small enterprise support ecosystem which can be helpful to come up with planning for the working capital business models.
Keywords: Effects, Grant, Small Business, Government Financial Support, Firm Revenue Performance
Aksemsettin Mah. Kocasinan Cad.
Erenoglu Is Merkezi
Fatih – Istanbul, TURKEY
Email: [email protected]
This work is licensed under a Creative Commons Attribution 4.0 International License.