The main objective of the present study is to investigate the risk factors influencing on construction firm’s project success in Pakistan. The study uses the partial least square structural equation modelling technique to analyse the data collected from 61 construction firms. The study finds positive impacts of design risk, financial risk, technical risk and labour risk on the success of the project. Alternatively, the current study finds no relationship between external risk factors and the success of the project. Furthermore, the current study suggests government and construction firms to consider the risk factors during the decision making for project implementation.

Correct application of the classical factorial F-test depends on normality and homogeneity of variance assumptions. If these assumptions are violated the type I error rate will be inflated and power of the test will be decreased. Therefore nonparametric statistical tests have been proposed to analyze the interaction effects in factorial designs. A simulation was conducted to investigate the effect of non-normality on type I error rate and power of the test of the classical factorial F-test and five nonparametric tests namely rank transformation (FR), Winsorized mean (FW), modifies mean (FM), adjusted rank transform (ART) and adjusted median transform (AMT) using program SAS 9.4 with 1,000 replications. The study used 2×2 factorial design with replications of 3, 4 and 6 making sample sizes of 12, 16, and 24, respectively and 3×3 factorial designs with replication of 3 making a sample size of 27 studied at 0.05 level of significance. As a results, when the normality of assumption is satisfied all six statistical tests have the ability to control type I error in all situations. The ART test cannot control type I error rate for 3×3 factorial design when sample size is 27 when normality assumption is violated. For power of the test, the F-test provided the highest test power when the normality of assumption is met. The ART and AMT tests provided approximately the same test power. The AMT and ART tests can be effectively used to analyse the interaction effect between factors A and B in 2×2 factorial design when the sample size is 12 and 16 or 24 respectively and the normality of assumption is not met. Moreover, the results showed that when sample sizes increased, all six statistical tests tended to increase the power of the test.

This paper proposes a new distribution named the negative binomial-weighted Lindley. The study uses the maximum likelihood estimation to estimate the parameters of the proposed distribution and compares the performance of the new method with other distributions. The study finds that the negative binomial-weighted Lindley distribution, obtained by the mixing the negative binomial distribution with the weighted Lindley distribution is another mixed negative binomial distribution and may provide an appropriate fit for data estimation with overdispersion. Some characteristics of the proposed distribution, such as mean and variance are also derived.

This study analyzes the tourism network and destinations after the COVID-19 pandemic using social network analysis (SNA). Analysis of 789 destinations in Thailand has found that the destinations are connected by 1,1175 tourism routes. The network is a sparse network with a low network density. It seems to have a scale-free property that reflects that most destinations have low connectivity and a small number of destinations have high connectivity. The network has a large average path length and low clustering coefficient. Different roles of destinations are identified based on degree, betweenness and closeness centrality. The findings draw implications for vitalizing the sector.

In a continuous manufacturing environment where production and consumption occur simultaneously, one of the biggest challenges is the efficient management of production and inventory system. In order to manage the integrated production inventory system economically it is necessary to identify the optimal production time and the optimal production reorder point that either maximize the profit or minimize the cost. In addition, during production the process has to go through some natural phenomena like random breakdown of machine, deterioration of product over time, uncertainty in repair time that eventually create the possibility of shortage. In this situation, efficient management of inventory & production is crucial. This paper addresses the situation where a perishable (deteriorated) product is manufactured and consumed simultaneously, the demand of this product is stable over the time, machine that produce the product also face random failure and the time to repair this machine is also uncertain. In order to describe this scenario more appropriately, the continuously reviewed Economic Production Quantity (EPQ) model is considered in this research work. The main goal is to identify the optimal production uptime and the production reorder point that ultimately minimize the expected value of total cost consisting of machine setup, deterioration, inventory holding, shortage and corrective maintenance cost.

A real inventory system for single item with specific demand characteristics motivates this works. The demand can be seen as two types of independent demand, where compound Poisson process describes the characteristics of each demand. The first type of demand is rarely occurred with relatively large size, while the second type of demand is often happened with relatively small size. In order to maintain inventory level, every time the first type of demand occurs a replenishment of stock is conducted which follows order-up-to-level inventory policy. In order to find the optimal inventory decision for that system, a mathematical model of the system is developed with the objective to minimize expected total inventory cost. Some of model assumptions are infinite replenishment, deterministic lead time, and completely backlogged shortages. To solve the model, it is then divided into two sub-problems and classical optimization technique is employed to help find the solution of each sub problem.

The firms and the industries still using the ways and means of promotion and publicizing the products have still not achieved the level of success as the modern means of social media is providing in creating a huge demand for their products. This study involves the modern means of communication agility promises success, development, and significance of the product in an efficient manner. Social media plays a vital role in creating a demand for the products by explaining the need of the product and a very effective source of creating a link among industries, firms, management, employees and especially the individual ones who come to know the skills and expertise. The impact of social media in strengthening the relationship with the customer has been very keenly observed and the findings show that such research has detailed that the use of social media has influenced the internal and the external capabilities. The data gathered in this study shows that the firms and the industries using the approach of social media have a revolutionary impact on building and strengthening the relationship between the customer and the management, employees. This study shows a strong bond between a firm and the customer using social media.

This study aims to identify and mitigate supply chain risks associated with organic rice in Thailand, based on the principle of supply chain risk management (SCRM). The risk measurement is performed using Best-Worst method (BWM) for ranking the criticality of different factors in order to find the appropriate ways for improving and developing new ideas for supply risk chain management. The study identifies 26 risk factors associated with the organic rice supply chain based on the literature and interviews with four experts. The order of risk priority in the organic rice supply chain in descending order (the top 5) is as follows: Lack of efficient equipment or machinery, Lack of organic rice mill, Lack of labor, Transportation cost, and Production cost. The SCRM guidelines of organic rice in Thailand include cost reduction and investment in infrastructure.

The objective of this research is to examine the factors that affect tourism investment in the CLMV countries (Cambodia, Laos, Myanmar, Vietnam and Thailand). This study employs panel data as quarterly data from 2000 - 2019. Data analysis employs the panel unit root test estimated by fixed effect estimation. The results revealed that the Minimum Loan Rate factor has a negative effect on tourism investment while the number of international tourists and Gross Domestic Product (GDP) positively affect tourism investment. Therefore, in each CLMVT country, the relevant authorities should determine a suitable Minimum Loan Rate (MLR), target tourism promotion as a single region and pursue policies that enhance the economy. Such policy should support employment in the tourism sector and enhance the economic system of the CLMVT countries.

This study considers a supply chain master planning problem in an uncertain environment where operating costs, customer demand, production capacity, manufacturer’s acceptable defective rate, and manufacturer’s acceptable service level are uncertain. Our supply chain consists of one manufacturer, multiple suppliers, and multiple distribution centers. While one objective is to minimize the total costs of logistics that consists of purchasing cost, production cost, and distribution cost, the other objective is to maximize total value of purchasing. These objectives are in conflict with each other. In this paper, the fuzzy multi-objective linear model is applied with α-Cut analysis to achieve the optimal supply chain master planning in an uncertain environment by balancing these two conflicting objectives. The α-Cut analysis is introduced to ensure decision-makers that the outcome satisfies their preferences based on a specified minimum allowed satisfaction value (α).