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This paper aims to present the results of energy management and optimization studies in one Turkish textile factory. In a case study of a print and dye factory in Istanbul, the authors identified energy-sensitive processes and proposed energy management applications.

Appropriate energy management methods have been implemented in the factory, and the results were examined in terms of energy efficiency and cost reduction.

By applying the methods for fuel distribution optimization, the authors demonstrated that energy costs could be decreased by approximately.

Energy management is a vital issue for industries particularly in developing countries such as Turkey. Turkey is an energy poor country and imports more than half of its energy to satisfy its increasing domestic demands. An important share of these demands stems from the presence of a strong textile industry that operates throughout the country.

This paper aims to examine the effects of lines of credit on a firm’s market timing behavior and the pricing of its seasoned equity offerings (SEOs). It shows that firms with lines of credit are more likely to time the equity market and receive less underpricing for their SEOs. It also shows that the propensity of firms with lines of credit to time the market is particularly significant for financially unconstrained firms. The results are robust to different measures of market timing and financial constraint, and these fill the gap in the literature that, to the best of the authors’ knowledge, has not examined the relation between lines of credit, market timing and value creation as related to equity offerings.

The paper first investigates the relationship between lines of credit and the probability of a firm issuing SEOs using a logistic model. The paper then investigates whether firms with lines of credit engage in market timing behavior using ordinary least square regressions with two-way cluster-robust standard errors (standard errors that are robust to simultaneous correlation along two dimensions, such as firms and time) with two measures of market timing and two measures for financial constraints. Finally, the paper examines the relationship between lines of credit and SEO underpricing.

It was found that firms with lines of credit are more likely to time the equity market, perhaps driven by the financing flexibility resulting from the existence of their lines of credit. This finding comes mainly from financially unconstrained firms, as such an effect is not observed among financially constrained firms with lines of credit. It is further shown that firms with lines of credit are more likely to experience less severe equity underpricing, perhaps owing to market timing behavior. The results provide evidence on how lines of credit may create value to a firm through its market timing.

The paper sheds new light on how lines of credit may create value to a firm through the market timing channel.

Aritificial intelligence (AI)-focused enterprises purpose to provide value-creating and differentiated products and services using innovative technologies. For this reason, it is aimed to examine the effects of value creation, intellectual property and organizational creativity variables to make evaluations to increase the success of such enterprises.

Random sampling method was used in the research. The population of the research consists of AI-oriented enterprises in technoparks. On the specified days, short-term visits and surveys were conducted face-to-face. Name and similar personal information was not taken in the research and participation was made on a voluntary basis. A sample size of 500 units is a sufficient size at the 0.05 significance level. SmartPLS (4.0.8.4) licensed software was used in the research.

As a result of the collected data, it has been supported by hypotheses that value creation, intellectual property and organizational creativity have positive effects so that artificial intelligence-oriented enterprises can be successful in performance criteria.

Since the research was conducted by collecting data from artificial intelligence-oriented enterprises in technoparks in Istanbul, it would not be correct to evaluate the analysis results by making generalizations. For this reason, it is recommended that similar studies planned to be conducted in the future should contribute to the literature by developing the research model, taking into account the limited situation in the sample.

According to the results of the analysis of the effects of value creation, intellectual property and organizational creativity in artificial intelligence-oriented enterprises, in order to increase the success of such enterprises, they should offer more value to their customers, protect their technologies and increase their innovation capacity.

Value creation, intellectual property, and organizational creativity in AI-focused enterprises are important topics in a rapidly growing industry such as AI-focused enterprises. Therefore, a research investigating these variables together offers a different perspective than previous studies.

The purpose of this paper is to examine the impacts of (non-renewable and renewable) energy consumption and trade on environmental pollution in an environmental Kuznets curve (EKC) setting in Turkey for the 1965–2016 period.

Besides conventionally used unit root tests, Zivot–Andrews unit-root test is also employed to account for a possible structural break. To investigate the interrelationships among the variables, the autoregressive distributed lag and the vector error correction methodologies are employed.

The results verify the EKC hypothesis. Moreover, increases in trade and non-renewable energy consumption rise carbon emissions in long run, while renewable energy consumption reduces it in both short- and long-run. The causality analysis reveals that there are bi-directional long-run causalities between non-renewable energy consumption and carbon dioxide emissions, and between trade and carbon dioxide emissions. Additionally, the neutrality hypothesis is valid for the renewable energy consumption-income nexus in both short- and long-run. For the non-renewable energy consumption-income nexus, the neutrality hypothesis holds only in short-run and the conservation hypothesis holds only in long-run.

This is the first study which incorporates both renewable energy consumption and trade into its environmental pollution model for Turkey. Moreover, by investigating short- and long-run causalities among the employed variables, more robust policy implications are put forward. Lastly, this study employs a longer sample period and considers a structural break in its models.

The purpose of this paper is to examine the many factors that affect the leverage decisions of publicly traded Australian companies, and tests to see whether these factors are reliably important. The relationship between these factors and the leverage decision is examined.

This study uses a multiple linear panel regressions to study the relationship between the factors and leverage.

The authors find a set of eight factors which are reliably important for capital structure decision making. These factors include: profitability, log of assets, median industry leverage, industry growth, market to book ratio, tangibility, capital expenditure, and investment tax credits. The empirical evidence indicates weakening support for the pecking order hypothesis and increasing support for the trade-off theory in Australia.

This paper examines the determinants of capital structure using Australian firms and provides a comprehensive empirical support for the capital structure theories.

This paper proposes the adoption of Industry 4.0 (I4) technologies and lean techniques for improving operational performance in the healthcare sector.

The research adopted a systematic literature review and feedback of healthcare professionals to identify the inefficiencies in the current healthcare system. A questionnaire was used to get feedback from the patients and the hospital staff about the current practices and issues, and the expected impact of technology on existing practices. Data were analysed using descriptive statistics, correlation analysis and multiple regression analysis.

The results indicate that I4 technologies lead to the improvement of the operational performance, and the perceptions about I4 technologies are made through the pre-medical diagnosis. However, a weak correlation between lean practices and healthcare operational performance compared to that of I4 technologies and operational performance indicate that lean practices are not fully implemented in the Sri Lankan healthcare sector to their full potential.

This study is limited to two government hospitals, with insights from only the doctors and nurses in Sri Lanka. Furthermore, the study is limited to only selected aspects of I4 technologies (big data, cloud computing and IoT) and lean concepts (value stream mapping and 5S). Therefore, recommendations on the adoption of I4 technologies in the healthcare sector need to be made within the scope of the study investigation.

The implementation of I4 technologies needs careful consideration of process improvement as part of the overall plan for achieving the maximum benefits of technology adoption.

The findings of the research can be used as a benchmark/guide for other hospitals to explore the adoption of I4 technologies, and how process improvement from lean concepts could influence the overall operational performance.