This study aims to analyze the effect of budget participation on the performance of the government apparatus of Palu City through budgetary slack with Culture kaili “Nosarara Nosabatutu” as moderating. This research was conducted in the regional apparatus organization of the Palu City Government in 41 regional work unit. Data were analyzed using Structural Equation Modeling with WARP PLS 7.0. The results show that budget participation has a positive effect on the performance of government officials, budget participation has a negative effect on budgetary slack and negative budgetary slack on the performance of the government apparatus. The results of this study also indicate that budgetary slack was a partial mediator between the effect of budget participation on the performance of local government officials. The Kaili culture variable “Nosarara Nosabatutu” cannot be proven as a moderator.

The primary objective of this paper is to investigate the relationship between total quality management practices (TQMP), supply chain management practices (SCMP), information technology capabilities, supply chain technology adoption and firm supply performance. In addition, the study also tries to investigate the mediating role of information technology capabilities and supply chain technology adoption in the relationship between TQMP, SCMP, and firm supply performance. The study is carried out on a sample of textile firms of Pakistan. To achieve the research objective, Smart PLS-3 is used for the analysis of the data gathered from the textile firms of Pakistan. The results of the study show a great deal of agreement with the hypothesized results. The information technology capabilities, supply chain technology adoption both appear to play mediators between TQMP, SCMP, and firm supply performance. The results of the study will be useful for policymakers and researchers to understand the emerging role of technology in strategic management and operational management.

Technologies of Artificial Intelligence (AI) are critical for future of the auditing profession. These technologies are actually vital tools that provide the auditing professionals with the means necessary for increasing the effectiveness and efficiency of their jobs. The aim of this study was to examine the effect of artificial intelligence technologies on audit evidence, from the point of view of certified auditors in information technology (IT) companies in Jordan. Descriptive research design was adopted in the study among 314 auditors. Structured questionnaire was used to obtain the information needed for the study. The findings of the study showed that expert system had a significant effect on the audit evidence. Neural network technology did not provide any significant effect on the audit evidence. The study recommended increased interest in artificial intelligence technologies by audit offices operating in Jordan because of its scientific importance in improving the collection of audit evidence.

This paper deals with the total tardiness minimization problem in a parallel machines manufacturing environment where tool change operations have to be scheduled along with jobs. The mentioned issue belongs to the family of scheduling problems under deterministic machine availability restrictions. A new model that considers the effects of the tool wear on the quality characteristics of the worked product is proposed. Since no mathematical programming-based approach has been developed by literature so far, two distinct mixed integer linear programming models, able to schedule jobs as well as tool change activities along the provided production horizon, have been devised. The former is an adaptation of a well-known model presented by the relevant literature for the single machine scheduling problem with tool changes. The latter has been specifically developed for the issue at hand. After a theoretical analysis aimed at revealing the differences between the proposed mathematical models in terms of computational complexity, an extensive experimental campaign has been fulfilled to assess performances of the proposed methods under the CPU time viewpoint. Obtained results have been statistically analyzed through a properly arranged ANOVA analysis.

The choice of capital structure has greatly contributed to the success of the firms in general and energy in particular. This study uses a sample data set of 250 energy firms over the period 2010-2019, and by using generalized least square (GLS) method to perform a survey. The main factors in this study include profitability, firm age, state shareholding and depreciation tax shield, etc. The study found that except firm growth, all factors including firm performance, age of firm, size of firm, asset structure, short-term solvency, and depreciation have significantly affected firm’s capital structure choice in the case of energy industry in a developing country. Furthermore, a positive effect was also found for size of firm and asset structure while a negative effect was detected for other factors such as firm performance, asset structure, firm age, short-term solvency, and depreciation. Through this research, we also conclude that the theory of pecking order, and the theory of representative cost are known as the basis for financial managers to build sound capital structures for businesses.

This paper investigates the role played by service quality at supplier-manufacturer dyad in small-medium manufacturing units, and presents a model to establish that contribution of both the supplier and manufacturer towards service quality could lead to satisfaction followed by loyalty. The research design for this study includes a combination of literature survey, exploratory interviews with practitioners, and a questionnaire survey conducted through interview schedule from 120 respondents working in different small-medium manufacturing units of North India. Structural equation modeling (SEM) is used for data analysis. The paper develops dual directional scales to evaluate service quality at supplier-manufacturer dyad and tests a set of four propositions. A model showing linkages of manufacturer (manufacturing unit’s) service quality with supplier service quality leading to satisfaction and loyalty is also developed. The model is empirically tested and is found to be fit. This study would be of interest to SME managers particularly engaged in ‘purchase’ function and researchers working on inter-firm supply chains in such units. This study recommends forming strong collaborative relationships with suppliers to achieve a win-win situation.

Altman Z score is an effective tool for measuring a company's financial strength and the possibility of bankruptcy. In this study, the Z score formula was utilized to measure the Indian automobile industry's financial soundness. The financial data of ten automobile companies listed in the National Stoke Exchange (NSE) was taken to analyze both original and emerging market formulae of the Altman Z score. Results suggest that companies of the industry listed in the NSE are financially sound. The study concluded that the Indian automobile industry is sound and robust, and the automobile companies are not prone to financial distress or bankruptcy in the near future.

Facility location models are observed in many diverse areas such as communication networks, transportation, and distribution systems planning. They play significant role in supply chain and operations management and are one of the main well-known topics in strategic agenda of contemporary manufacturing and service companies accompanied by long-lasting effects. We define a new approach for solving stochastic single source capacitated facility location problem (SSSCFLP). Customers with stochastic demand are assigned to set of capacitated facilities that are selected to serve them. It is demonstrated that problem can be transformed to deterministic Single Source Capacitated Facility Location Problem (SSCFLP) for Poisson demand distribution. A hybrid algorithm which combines Lagrangian heuristic with adjusted mixture of Ant colony and Genetic optimization is proposed to find lower and upper bounds for this problem. Computational results of various instances with distinct properties indicate that proposed solving approach is efficient.

The purpose of this study is to create a sustainable business model of Islamic banks in Indonesia through financial and non-financial aspects with financial performance as a mediate variable. The study uses quantitative approach by collecting secondary data of Islamic Banks from financial statements and annual reports over the period 2010-2018. The population of this study is 9 (nine) Islamic banks and the sample of research uses the census method. Data processing methods uses Partial Least Square. The results of the study stated that corporate governance has a significant effect on financial performance, intellectual capital has a significant effect on financial performance and company size has a significant effect on financial performance, but corporate governance has no effect on sustainable business. In addition, intellectual capital has a significant effect on sustainable business but company size has no effect on sustainable business. Moreover, financial performance has a significant effect on sustainable business, financial performance mediated the effect of corporate governance on sustainable business, financial performance partially mediated the effect of intellectual capital on sustainable business and financial performance mediated the effect of company size on sustainable business.

Recently, learning effects have been studied as an interesting topic for scheduling problems, however, most researches have considered single or two-machine settings. Moreover, learning factor has been considered for job times instead of setup times and the same learning effect has been used for all machines. This paper studies the m-machine no-wait flowshop scheduling problem considering truncated learning effect in no-wait flowshop environment. In this problem, setup time is a function of job position in the sequence with a learning truncation parameter and each machine has its own learning effect. In this paper, a mixed integer linear programming is proposed for the problem to solve such problem. This problem is NP-hard so an improved genetic algorithm (GA) and a simulated annealing (SA) algorithm are developed to find near optimal solutions. The accuracy and efficiency of the proposed procedures are tested against different criteria on various instances. Numerical experiments approve that SA outperforms in most instances.