پژوهشنامه بازرگانی
پیاپی 91 (تابستان 1398)

This paper examines the own and cross price elasticities of the labor force demand for two size firms: 10-49 employees and more than 50 employees. Estimation of elasticities is done in two steps: firstly, the effect of some variable will be regressed on labor income share. In second step, by using of previous estimation, own price and substitution elasticities of the labor will be calculated. In this study, for estimation, the Fractional Panel Probit technique has been employed for the period of time from 2004 to 2014 and at the provincial level. The results of estimation for both groups shows a negative relationship between tax, value of raw material and premium paid with labor income share. There is a positive sign for output-employment elasticity. The results show own price elasticity is negative and cross elasticity of capital price and labor demand reveals a substitution effect in small firms. As Iran’s labor market is suffering from labor demand shortage and high unemployment, it is suggested that the economic policymaker should eliminate production barriers, care about increasing production capacity and facilitate the supply of raw materials.

Multiregional economic models that present a set of regional economies in a continuous manner and show cross-regional interactions require calculating the export of each region to other regions and import of each region from other regions. In the process of survey inter-regional relations and creating multi-regional input-output, the missing link is the estimation of inter-regional trade. In this study Iran was divided into nine regions, and using the CHARM method and Gravity model with the aim of estimation  of regional and inter-regional trade, the total volume of trade between the two regions and the trade of each part of the region was calculated with other regions. Accordingly, the total volume of Iran’s interregional trade is 858.133 billion rials. The interregional trade about regions that are geographically located in the center of the country are higher than the non-central regions of the country, such that the highest volume of interregional trade is related to the Alborz Jonubi region with the volume of 173,637 billion Rials and the smallest volume of interregional trade related to the Azarbayjan area with the volume of 68.392 billion Rials. The largest volume of interregional trade, in the Costal-North area is in the agricultural sector, the Azerbaijan region is in the industrial sector, the Zagros region is in the agricultural sector, the Khuzestan region is in the mining sector, the Fars region is in the industrial sector, the Alborz region is in the service sector, the Central region is in the Industry sector, the South-East region is in the industry sector and in the Khorasan region is in the Service sector. In addition, the international trade of the regions was estimated by sector, and with combining the results of the regional and international trade estimates, policy recommendations were presented for each region.

Nowadays, the main part of countries' economic power has been resulted from acquiring knowledge and applying it to produce innovative up to date products in order to gain competitive advantages in domestic and foreign markets. One of the effective elements for achieving such a goal is knowledge workers. The purpose of this study is investigating the effect of knowledge workers on the innovative goods and services exports with considering the moderating effect of competition in developed and developing countries from 2011 to 2016. Data of selected sample countries has been extracted from the Global Innovation Index reports. The panel method is used by applying Eviews software. The results showed that not only knowledge workers have positive and significant impact on export of innovative goods and services of those countries, but also in both of developed and developing countries, competition plays a moderating role on the relation between knowledge workers and exporting innovative goods and services.

Clients as one of the main cornerstones of today's companies are in a competitive environment and it is very important as a strategic topic for companies, because one customer satisfation is not necessarily the satisfaction of another customer. because the personality of the people and their needs are also different in different situations. The purpose of this research is Identification and Analysis of Customer Satisfaction Quality Criteria Using the FANP Fuzzy Network Analysis Model. The present study is descriptive in nature and in terms of the purpose of this research is applied. In order to analyze the collected data, the network analysis method (ANP) has been used. Based on a thorough study of the theoretical and theoretical issues, 28 sub-components were identified in the 5 main component and were designed in a checklist for the panelists and panel members in the qualitative section of the research. Participants in this section were 20 marketing elites who contributed to the researcher in two Delphi rounds. In the small part after confirmation of the sub-components, a researcher-made questionnaire was distributed among 30 managers and experts in the field of valve industry. According to the fuzzy network analysis, first, the ranking of the components was determined and then the difference between the status and the situation Desirable to identify the important factors of customer satisfaction. The results of the research in the qualitative section of the total of 28 identified components confirmed 22 sub-components  on the basis of fuzzy network analysis. First, the highest obtained weight belonged to the criterion of consideration of the needs and demands of the customers, and secondly it was determined there are significant differences between the identified sub-components between the status quo and the desired satisfaction of customers.

Because of the increased competition at the market, the researchers, in order to respond to the rising marketing expenses, have started to study the brand investment rate which results in the achievement of the competitive advantage, especially in the service industries. Furthermore, the new data sources in the constantly changing world makes the scholars to focus on the dynamic functions of the different kinds of the investment in brand management to improve the decision-making process. The goal of this study to design a dynamic model for the brand management investment through the influential factors on the brand equity (Brand Awareness, Brand Association, Perceived Quality, Brand Loyalty) in Alborz Insurance Company to predict the behavior of these factors in a spectrum of a 6-year time period using Vensim Software. In this article, after drawing the flow-accumulation map, model's sensitivity and policy will be analyzed and the result will be used to prepare the improvement scenario. In this model, with changing the different kinds of investment (media advertisement, public relations, direct marketing and price promotion) three scenarios of basic, optimistic and pessimistic will be compared which the optimistic scenario shows that with increasing the percentage of the total investment, the band equity will have 7 percent increase.

In some cases, software companies condition the sale of computer software on acquiring hardware components or integrate computer softWare with complementary software and hardware when designing products. Complementary software and hardware must be interoperable in terms of functionality. The specific nature of computer software causes network effects and mass production savings in software industry. The majority of software right abuse arises when the developer conditions licensing a software on the complementary software and hardware that makes it impossible to buy these products independently. Such condition in license agreements of computer software violates U.S antitrust laws provided that the developer has tied independent products and the seller has essential market power in the created products market. This condition has different competitive effects. In the Iranian law, the Act on the implementation of article 44 of the constitution which has stated the basic rules of competition, has not dealt with the issue perfectly and there are provisions in the Act on computer software developers and its by-law on interoperability. Given the absence of independent studies in this field, analysis of rules can lead to clarification of the subject.

The trade secretes is very important for the owner of secretes specially for the traders.  Non-disclosure contract of trade secrets is used to prevent disclosure of trade secrets and, conducting it makes it easier to prove commitment to secrecy by the loser and predicting contract performance guarantee such as indemnity, compensation is guaranteed in the better way, so it has taken a special place and importance so that it can be considered as the most important predictive and contractual support tool. However, to what extent the contract can be considered as an appropriate protective tool for the holder of trade secrets is questioned and worried by traders. In this descriptive-analytical research , the advantages, application, performance guarantee and the effects of this contract on the parties and the second parties relying on the instance contract of international chamber of commerce we concluded that although the advantages of using this contract as a protective standard for the owner is undeniable, but one can’t rely on it as a guarantee tool , rather it is necessary to view this contract as a minimum protective lever and other approaches is used as a complementary.

Predicting financial distress is an important phenomenon for investors, creditors and other users of financial information. Determining the probability of a company’s distress before occurrence of distress and bankruptcy is considered a very interesting and attractive subject and can be useful for both managers, and investors and creditors. In this study, using the data of 1350 year- company during the period 2008 to 2016 in industry and mining sector in Iran, the factors affecting financial distress and predicting it through Intelligence Algorithms methods (decision tree, support vector machine, and Bayes classification methods) have been studied. The results of the study indicate direct impact of financial risk and inflation, and inverse` impact of the ratio of non-executive directors, stock returns, and the ratio of operating cash flow on financial distress. The results also show that decision tree method, using financial and economic data, has higher efficiency in predicting financial distress compared to Bayes classification method and support vector machine.