Search results

This chapter presents a study on the work of commercial diplomats as international business promoters at foreign posts. Research has largely overlooked the actual roles and activities of commercial diplomats in explaining the effectiveness of commercial diplomacy and international business support. In this study, it is assumed that commercial diplomats’ behavior is influenced by informal institutions. Face-to-face semi-structured interviews with 23 commercial diplomats at foreign posts from different countries were conducted and analyzed. The results show three different types of role behavior and differences in proactivity per type. Informal institutions such as background, skills, and experience, cultural differences, and the working environment suggest to explain the differences in levels of proactive international business support behavior of commercial diplomats. Further research is needed to assert these findings.

The purpose of this paper is to present a new constrained optimization algorithm based on a particle swarm optimization (PSO) algorithm approach.

This paper introduces a hybrid approach based on a modified ring neighborhood with two new perturbation operators designed to keep diversity. A constraint handling technique based on feasibility and sum of constraints violation is adopted. Also, a special technique to handle equality constraints is proposed.

The paper shows that it is possible to improve PSO and keeping the advantages of its social interaction through a simple idea: perturbing the PSO memory.

The proposed algorithm shows a competitive performance against the state‐of‐the‐art constrained optimization algorithms.

The proposed algorithm can be used to solve single objective problems with linear or non‐linear functions, and subject to both equality and inequality constraints which can be linear and non‐linear. In this paper, it is applied to various engineering design problems, and for the solution of state‐of‐the‐art benchmark problems.

A new neighborhood structure for PSO algorithm is presented. Two perturbation operators to improve PSO algorithm are proposed. A special technique to handle equality constraints is proposed.

Achieving Sustainable Developments Goals (SDGs) is main agenda of any democratic government. The demand for needs of the society is increasing day by day due to increasing globalization and rapid transformation in all spheres of the society, and as a result, agriculture has shifted from a situation where food is primarily considered as a national concern with high self-sufficiency goals to a situation, where food can be traded subject to high degree of vertical integration of value chain. This study attempts to examine first, how far the state Tripura has developed toward to achieving its SDGs; so that Central dependency of the state would be reduced; second, the impact of globalization on its sustainable development; and, third, the possibility of development in different sectors of the economy toward fulfilling the SDGs through globalization. It observes that the state is in the take-off stage; it needs to go long way to make it developed. The state has lot of potentialities for its sustainable development.

Big 4 professional services firms increasingly lay claim to recruiting and including staff of diverse genders, cultures, ages and sexualities. Drawing on Foucauldian insights, this study explores how LGBTIQ+ staff navigated shifting technologies of client power, at the time marriage equality was legislated in Australia.

This article explores changing experiences of LGBTIQ+ staff and allies, through 56 semi-structured interviews undertaken through 2018–2019.

Technologies of client power were central to shaping workplace experiences for LGBTIQ+ staff. However, each firm was also keen to carve unique and bold responses to changing societal attitudes regarding sexuality and gender. These progressive moves did not sit comfortably with all clients, and so this article provides insight into the limitations of client privilege within professional services firms. For staff, this increasing complexity of sometimes opaque, contradictory and shifting technologies of client and firm power, enabled agency to explore a sense of self for some, but continued to exclude others.

Little attention has been directed to exploring challenges for staff of sexual and gendered diversity within professional services firms, or to exploring how staff navigate changing perceptions of client power.

Lester and Wolff (2013) find little empirical support for the Austrian business cycle theory. According to their analysis, an unexpected monetary shock does not alter the structure of production in a way consistent with the Austrian view. Rather than increasing production in early and late stages relative to middle stages, they find the opposite – a positive monetary shock typically decreases production in early and late stages relative to middle stages. We argue that the measures of production and prices employed by Lester and Wolff (2013) are constructed in such a way that makes them inappropriate for assessing the empirical relevance of the Austrian business cycle theory’s unique features. After describing how these measures are constructed and why using ratios of stages is problematic, we use a structural vector autoregression to consider the effects of a monetary shock on each stage of the production process. We show that, with a clearer understanding of what is actually being measured by the stage of process data, the results are consistent with (but not exclusive to) the Austrian view.

This research investigated the market conditions caused by IPO advertising by examining the impact of IPO advertising, based on the US stock market from 1986 to 2009. The relationship between advertising intensity in the IPO year and the degree of IPO underpricing was examined. It was found that an increase in advertising intensity around an IPO event increases the initial returns. Simultaneously, however, advertising intensity around an IPO event also increases the degree of overvaluation, which raises the question as to whether advertising serves primarily as a mechanism to convey a firm’s true value to investors. The theoretical valuation of IPO and the relation between IPO advertising and the degree of stock overvaluation are discussed. Based on the Peasnell’s (1982) residual-income valuation framework (henceforth RIV), IPO advertising was proved to cause stock price to be more overvalued in the secondary market: a positive relationship was found between advertising and the degree of stock overvaluation relative to its theoretical value. Accordingly, an alternative hypothesis, that advertising inflates the short-run stock price, was proposed. The results of this study are consistent with the view of Purnanandam and Swaminathan (2004), namely that the stock price of newly listed firms can be overvalued.

Starting in March 2020, Indonesia had the COVID-19 pandemic. Furthermore, this situation has decreased the utilization of highways due to complying with the government regulation, including work from home and large-scale social restrictions to reduce the spreading the corona virus. There are three highway companies listed on Indonesia Stock Exchange such as CMNP, META, and JSMR. On the other hand, the research about the financial performance and the financial distress prediction in Highways sector, especially in Indonesia is not available during the COVID-19 pandemic. This research is aimed to evaluate the financial distress by the Zmijewski model with two criterions: bankrupt and non-bankrupt zone and the financial performance by state-owned enterprise (SOE) rating with three criterions: healthy, less healthy, and unhealthy condition. The period of research is Q1 2019 – Q1 2020 as the period before the COVID-19 pandemic and Q2 2020 – Q2 2021 as the period during the COVID-19 pandemic. The study concludes that all highway companies was in non-bankrupt zone by the Zmijewski model for both before and during the COVID-19 pandemic. In addition, based on SOE rating on average for the period before the COVID-19 pandemic, CMNP, META, and JSMR achieved rating consecutively BBB, BBB, and BB. Meanwhile, on average, for the period during the COVID-19 pandemic, CMNP, META, and JSMR achieved ratings consecutively BB, BB, and B.

This chapter shows how to identify the characteristics of borrowers that are part of a credit scoring model. The credit risk scoring model is an important tool for evaluating credit risk associated with customer characteristics that affect defaults. This research was conducted at a financial institution, a subsidiary of a commercial bank in Indonesia, to answer the challenge of determining the feasibility of providing financing quickly and accurately. This model uses a logistic regression method based on customer data with indicators of demographic characteristics, assets, occupations, and financing payments. This study identifies nine variables that meet the goodness of fit criteria, which consist of WOE, IV, and p-value. The nine variables can be used as predictors of default probability: type of work, work experience, net finance value, tenor, car brand, asset price, percentage of down payment (DP), interest, and income. The results of the study form a risk assessment model to identify variables that have a significant effect on the probability of default.

This chapter develops a no-arbitrage, futures equilibrium cost-of-carry model to demonstrate that the existence of cointegration between spot and futures prices in the New York Mercantile Exchange (NYMEX) crude oil market depends crucially on the time-series properties of the underlying model. In marked contrast to previous studies, the futures equilibrium model utilizes information contained in both the quality delivery option and convenience yield as a timing delivery option in the NYMEX contract. Econometric tests of the speculative efficiency hypothesis (also termed the “unbiasedness hypothesis”) are developed and common tests of this hypothesis examined. The empirical results overwhelming support the hypotheses that the NYMEX future price is an unbiased predictor of future spot prices and that no-arbitrage opportunities are available. The results also demonstrate why common tests of the speculative efficiency hypothesis and simple arbitrage models often reject one or both of these hypotheses.

This study is intended to investigate the volatility patterns in Bombay Stock Exchange Limited Sensitivity Index (BSE Sensex) based on time series data collected for 10 years period of time. To reach out the predefined objectives of the study, the authors have employed generalized autoregressive conditional heteroscedastic models. The study revealed that the presence of heteroscedasticiy is found in BSE Sensex. Further, the model produced highly accurate results when the researchers compared the estimated results from actual. Furthermore, the volatility of BSE Sensex has shown the features of clustering and significant time varying. Moreover, the model has indicated that there is a positive correlation between daily stock returns and the BSE Sensex volatility.