A new logistic model of market information asymmetry reduction in Poland

Gołembska, Elzbieta Article A new logistic model of market information asymmetry reduction in Poland Logistics Provided in Cooperation with: MDPI – Multidisciplinary Digital Publishing Institute, Basel Suggested Citation: Gołembska, Elzbieta (2021) : A new logistic model of market information asymmetry reduction in Poland, Logistics, ISSN 2305-6290, MDPI, Basel, Vol. 5, Iss. 1, pp. 1-19, https://doi.org/10.3390/logistics5010005 This Version is available at: https://hdl.handle.net/10419/310130 Standard-Nutzungsbedingungen: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden. Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen. 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A New Logistic Model of Market Information Asymmetry Reduction in Poland. Logistics 2021,5, 5. https://doi.org/ 10.3390/logistics5010005 Received: 9 December 2020 Accepted: 5 January 2021 Published: 14 January 2021 Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. Copyright: © 2021 by the author. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/). Department Finance and Banking, WSB University of Poznanul, Powstancow Wielkopolskich 5, 61-895 Poznan, Poland; [email protected] Abstract: The article presents the first theoretical and empirical estimation of the role of logistics in mitigating the effects of market information asymmetry in Poland. Following a review of international (Akerlof, Spencer, Stiglitz) and Polish literature (Gołembska, Gruszecki, Stradomski), a new logistic model of information asymmetry (LMAI) is presented. The article attempts an empirical verification of this model using the results of studies conducted in Polish firms in the period 2000–2018. The studies examined the efficiency and effectiveness of logistics management, with a particular focus on logistics infrastructure expenditure, balance-sheet inventories, and logistics costs. The computation of the LMAI indicator, based on averaged data provided by manufacturers, distributors and service firms, enabled the estimation of the impact of logistics management on reducing the effects of information asymmetry, and showed the differences of this impact in individual industries including the pharmaceutical, tourist, transport and food distribution industry. Keywords: logistic model of information asymmetry; sources of information asymmetry; transaction costs; logistics infrastructure; logistics costs; logistification; strategic alliances; internationalization; transnational corporations 1. Introduction The importance of logistics in international business derives not only from its interdisciplinary nature, but also from the fact that it has the potential to contribute to a company’s success. What is more, a new concept known as “logistification” (Fabbe-Costes and Rouquet, 2019 [ 1 ]) has now emerged, which refers to the rapid development of logistics in all spheres of human economic and non-economic activity. Yet in the twenty-first century, international business activity continues to be disrupted by information asymmetry in global supply chains. Various international authors and Polish writers (Gołembska 2008), have argued that logistics written into a corporate strategy may have a positive influence on reducing serious effects of market information asymmetry. Subsequently, this argument has been realized as a new logistics paradigm, and in 2015, Banaszyk and Gołembska [ 2 ] proposed a new model of the role of logistics in reducing the consequences of information asymmetry, which they called the logistic model of information asymmetry (LMAI). To explain the concept, the following hypothesis is put forward: Hypothesis 1 (H1). Modern company logistics play a significant role in reducing market information asymmetry. To verify this hypothesis, we formulated the following two research questions: 1. Does logistification of the world economy have a role in limiting the scale of market information asymmetry? 2. What elements of the logistics process in a firm singularly contribute to the reduction in the consequences of market information asymmetry? Logistics 2021,5, 5. https://doi.org/10.3390/logistics5010005 https://www.mdpi.com/journal/logistics Logistics 2021,5, 5 2 of 19 This paper is divided into two parts. The first part presents a literature review considering the theory and nature of market information asymmetry in the context of the growing logistification of the world. The synthetic measure of information asymmetry proposed by the Polish scholar Kubiak [ 2 ] is presented, together with the first attempt to verify the validity of this indicator in nine major industries of the Polish economy. In the second part, the article describes the role and significance of logistics in mitigating the consequences of market information asymmetry in modern-day companies. In order to quantify such influence, the theoretical formula for a logistics model of information asymmetry (LMAI) is proposed. This model is subsequently subjected to empirical verification, and the findings lead to the formulation of conclusions about the practical application of the model in business enterprises. The major parameters processed in the model include the value of capital investments in logistics infrastructure, the value of inventories in company assets, and the costs of logistics. 2. The Nature of Market Information Asymmetry: A Literature Review Market information asymmetry occurs when a firm has knowledge about itself but this knowledge is not readily available to other firms. This results in an obvious knowledge imbalance between trading partners in the market. Information asymmetry may be perceived as a social phenomenon, but primarily it is an economic fact that is empirical and measurable by qualitative and quantitative methods. Whether objectively or subjectively seen, information asymmetry is a sequence of signals that are difficult to measure. Consequently, the nature of this phenomenon lies in the fact that it concerns not only the difference in access to information between two firms, but also limitations resulting from understanding and processing the available information. In the theory of economics, early methods for measuring inequality in the access to market information in the context of company management, began to emerge in the 1960s and 1970s. The term “information asymmetry” was introduced to the theory of economics by James Mirrlees [ 3 ], who in 1996 was awarded a Nobel prize for his studies on information asymmetry between private firms and the government. In one of the first information asymmetry models, Akerlof [ 4 ] reflects on “adverse selection” as a result of information asymmetry between firms. Here, he also claims that such market failure leads to uncertainty about the quality of transacted goods or services, which in turn results in the dominance of low-quality products. The author suggests there should be some government intervention in order to eliminate the risk of dishonest acts between better informed firms and their less informed transaction partners. Spence [ 5 ] believed that firms themselves should mitigate the effects of information asymmetry by raising the quality of their products, providing guarantees for the goods and services offered, and manifestly signalling the high quality of their management personnel. In his considerations, Joseph E. Stiglitz [ 6 ] came to the radical conclusion that it is not true that market competitiveness is a sufficient condition for rational human resource management, thus questioning one of the fundamental principles of the classical economy. He justified his view by arguing that information asymmetry raises the fixed cost of gaining information, which in turn limits the competitiveness of a firm in the market. The works of these three authors combined laid the foundation for the general theory of markets under asymmetric information. In 2001, Akerlof, Spence and Stiglitz were jointly awarded the Nobel prize for justifying the thesis that deviations from rationality at the microeconomic level result in macroeconomic deviations. As a consequence, the whole economy of a given country achieves the point of balance below the effective utilisation of resources. The first step in theoretical and empirical studies of market information asymmetry is to define the causes of such asymmetry. These can be divided into objective/external and subjective/internal. As stated before, the objective causes relate to both the differences in the access to information between market participants, and difficulties in the interpretation of information. The subjective/internal causes can be found in the psyche of managers, Logistics 2021,5, 5 3 of 19 who in their pursuit of company profit maximization, act consciously or subconsciously to create such asymmetry. Internal reasons also include excessive self-confidence, the illusory truth effect, and the tendency to moral hazard. Synthetically, the causes of market information asymmetry can be presented as Figure 1. Logistics 2021, 5, x FOR PEER REVIEW 3 of 17 The first step in theoretical and empirical studies of market information asymmetry is to define the causes of such asymmetry. These can be divided into objective/external and subjective/internal. As stated before, the objective causes relate to both the differences in the access to information between market participants, and difficulties in the interpretation of information. The subjective/internal causes can be found in the psyche of managers, who in their pursuit of company profit maximization, act consciously or subconsciously to create such asymmetry. Internal reasons also include excessive self-confidence, the illusory truth effect, and the tendency to moral hazard. Synthetically, the causes of market information asymmetry can be presented as Figure 1. Figure 1. Causes of market information asymmetry. In Poland, theoretical and empirical studies of the causes and effects of market information asymmetry began in the 2000s. The authors of these studies, Gruszecki [7], Stradomski [8] and Noga [9], address the issue of imperfect information within the framework of business enterprise theory, and confront it with neoclassical theories. They agree that information asymmetry is a major factor hampering a firm’s performance. According to Gruszecki, modern theories of business enterprise take into account the cost of obtaining information, and acknowledge the asymmetric character of information procurement, which is due to both language differences and delays between the time that information becomes available and the time of decision making (e.g., investment decisions). Therefore, according to the author, the information asymmetry phenomenon should be considered in the broad context of business enterprise theory, and particularly, in the context of transaction cost, contract and agency theories. The transaction cost approach was developed, as we know, by Williamson [10], who pointed out that the differences in transaction costs, both ex ante and ex post, determine what a firm produces itself and what it sources from Figure 1. Causes of market information asymmetry. In Poland, theoretical and empirical studies of the causes and effects of market information asymmetry began in the 2000s. The authors of these studies, Gruszecki [ 7 ], Stradomski [ 8 ] and Noga [ 9 ], address the issue of imperfect information within the framework of business enterprise theory, and confront it with neoclassical theories. They agree that information asymmetry is a major factor hampering a firm’s performance. According to Gruszecki, modern theories of business enterprise take into account the cost of obtaining information, and acknowledge the asymmetric character of information procurement, which is due to both language differences and delays between the time that information becomes available and the time of decision making (e.g., investment decisions). Therefore, according to the author, the information asymmetry phenomenon should be considered in the broad context of business enterprise theory, and particularly, in the context of transaction cost, contract and agency theories. The transaction cost approach was developed, as we know, by Williamson [ 10 ], who pointed out that the differences in transaction costs, both ex ante and ex post, determine what a firm produces itself and what it sources from the marketplace. Here, we must clearly underline the fact that transaction costs can be significantly reduced relative to market levels through logistic management. In logistics, transaction costs are fundamentally important. Transaction costs also lie at the foundation of both contract theory and agency theory. In contract theory, a corporation is just a collection (nexus) of contracts entered into by a firm in order to gain control over its resources. As Hart [ 11 ] points out, contracts must be intelligible Logistics 2021,5, 5 4 of 19 not only to the contracting parties, but also to outsiders (e.g., courts) who may require certain knowledge about the specificity of the environment in which the parties operate. Finally, according to Gruszecki (op. cit.) both the transaction cost concept and the contractual approach are truly developed further within the agency theory. Here, similar to transaction costs, information asymmetry occurs both ex ante and ex post. Agency theory describes the relationship between business principals, who act in their own interest, and agents representing their principals in carrying out contracts. This relationship gives rise to information asymmetry, as agents enjoy full access to information and can use it to their advantage. Thus, in a logistically managed firm, information asymmetry affects transaction costs both at the contract preparation stage (ex ante), and during the fulfilment of the contract (ex post). The studies by the Polish authors outlined above concern the theory of the business enterprise; their findings need further research and empirical verification. Kubiak [ 12 ] was among the first Polish authors to undertake empirical studies of market information asymmetry. Using the linear ordering method, he studied the impact of information asymmetry on the capital structure in major Polish industries in the period 2002–2008. It is worth noting that both the methodology and findings of the study have provided valuable inspiration for developing new research methods to investigate the role of logistics in mitigating the effects of market information asymmetry. Briefly, the methodology used by Kubiak is a multidimensional comparative analysis involving a set of quantitative data (variables) processed according to predefined criteria in order to estimate information asymmetry due to various reasons and conditions. In this method, the synthetic measure of information asymmetry (SMAI) is computed based on the distance between an observed object and the model object. The model object is the maximum value of a given indicator in the entire period covered by the study, i.e., 2002–2008. The following formula is used: SMAI =v u u t n ∑ j=1 Wj·Xij −Xoj2(i=1, 2, . . . n) where: SMAI—the value of the synthetic measure of information asymmetry for the i-th object Wj—weight assigned to the particular object X oj —model object–max (X ij ), i.e., the maximum value of the j-th variable in the period 2002–2008 The study was based on the Main Office of Statistics (GUS) data and concerned major Polish industries. The results are as follows (Table 1): Logistics 2021,5, 5 5 of 19 Table 1. Synthetic measure of information asymmetry (SMAI) by industry (%), 2002–2008. No. Industry Name Synthetic Measure of Information Asymmetry (SMAI) Median Max Min Standard Deviation 1. Pharmaceutical industry 3.419 2.181 20.875 1.267 3.533 2. Services (intangible) 3.343 2.394 27.778 0.231 4.404 3. Machine industry 2.947 2.479 18.696 0.827 1.755 4. Trade and hospitality 2.704 2.391 19.183 0.439 1.635 5. Wood processing industry 2.534 2.216 21.226 0.309 1.741 6. Transport and logistics 2.376 2.179 28.323 0.660 1.805 7. Power generation 1.853 1.769 13.639 0.459 1.290 8. Purification and distribution of potable water, waste management 1.906 1.866 5.589 0.623 0.675 9. Mining and quarrying industry 1.845 1.996 3.917 0.179 0.725 Source: Author’s own overview based on Kubiak (op. cit) page 155. These very interesting and valuable findings of the 2002–2008 study provide an initial but important overview of the scale of information asymmetry in the respective industries of the Polish economy. The highest and the lowest values of the SMAI indicator are especially notable. The pharmaceutical industry is one of the business sectors with the highest degree of information asymmetry, perhaps due to its very specialised nature which requires specialist knowledge, particularly in investment decision making. In turn, a high degree of information asymmetry in the services industry reflects the high share of intangibles in the balance sheets, such as intellectual property or patents. At the other extreme there are industries such as mining and quarrying, power generation, water purification and distribution, or waste management, which are characterised by a low degree of information asymmetry. These are traditional, long-term industries with a controlled flow of information that are subject to high levels of regulation. Their business is regulated by special legislation and concessions. In a way it can be said that the results with respect to the latter group of industries confirm Akerlof’s observation that in some cases governmental intervention can mitigate market information asymmetry. At this point it seems appropriate to pose a question as to why the new phenomenon of logistification is so relevant to reducing the consequences of market information asymmetry. There are at least three explanations of this relationship: 1. The flourishing logistics industry, where value offered to client strictly depends on operational excellence. 2. The versatility and universality of logistics, which in turn poses strategic challenges for clients. In this respect, its particular role is attributed to the following [13]: •Strategy of creative logistics: management of change, creating innovative methods of evaluating logistics effectiveness • Strategy of pervading logistics: acquiring superior logistics competencies through information exchange • Strategy of systemic logistics: implementing logistic audits, identification of profit centres and added value sources. 3. Wide access to logistics training, not least because logistics has now become part of management science. A special feature of specialist logistics training is the ability to combine the personnel function of human resource management with the requirements of logistics management [ 14 ]. As studies conducted in Polish firms have shown, logisticians are characterized by high motivation in the administration of logistics tasks and creativity with respect to European requirements. Logistics 2021,5, 5 6 of 19 As mentioned before, in Poland the aim of research on the theory of market information asymmetry was to describe this phenomenon in the context of eliminating information imperfections and their impact on the condition of Polish firms. 3. The Role of Logistics in Reducing the Effects of Market Information Asymmetry—The Measuring Method In view of the discussion above, we might consider the question of why it is that logistics can have a role in mitigating the effects of market information asymmetry? In answering this question, we must first take note of the three fundamental reasons behind the increased role of logistics as the firm’s strategy in the modern global economy. These are [15]: 1. Intensified internationalization of enterprises in the twenty-first century, with a special role attributed to transnational strategies for company development 2. Dynamic increase of the number and quality of logistics services globally 3. The steadily growing role of strategic alliances formed by logistics and transport firms. With regard to point no. 1, the dynamic growth of international logistics stems from the interdisciplinary nature of globalized business (Table 2). Further, besides finance, technology, innovation and prices, logistics is a factor that determines the effectiveness of international operations. However, the necessary condition for including logistics in the firm’s strategy is the internationalization of business [16]. Table 2. Forms and examples of the internationalization of markets, institutions and economic instruments. Form of Internationalization Examples Internationalization of markets 1. Internationalization of markets for goods and services 2. Internationalization of factors of production, such as capital, workforce, technical knowledge, the natural environment Internationalization of institutions and organizations 1. Internationalization of national business and political institutions 2. Internationalization of institutions supporting international trade: banks, insurance companies, telecoms companies, international organizations Internationalization of economic policy instruments 1. Internationalization of tariff and non-tariff instruments regulating exports and imports 2. Internationalization of pressure group activities, e.g., consumer or producer protection organisations In other words, the internationalization of markets is the process of reducing the separation of markets for goods and services and the factors of production. Therefore, we can identify three forms of logistics internationalization, i.e., the management of international global chains, namely [17]: 1. Internationalization of logistics processes, from simple operational tasks to logistics as company strategy 2. Internationalization of markets for goods and services through global logistics services, including outsourcing and offshoring 3. Internationalization of logistics management in firms and transnational corporations through implementing modern methods of strategic management. Logistics 2021,5, 5 7 of 19 Particularly noteworthy are the innovative technologies that support logistic processes, such as [18]: •Artificial intelligence (AI) •Augmented reality (AR) •Self-driving vehicles (SDV) •Robotics (RO) The systematic development of international logistics markedly accelerates internationalization of firms, and consequently, the flows of factors of production in global supply chains. In the classic Bartlett and Ghoshal model [ 19 ], transnational strategies were formed when global integration increased along with local initiative. A typical example of such transnational strategy is the one pursued by the Ford Motor Company, where every logistics manager is responsible for global integration in the supply chains. Further, the effectiveness of transnational strategies has been attributed to their basic components, which are [20]: •Discriminating competencies, including logistics competencies •Geographic reach of logistics operations •Diversification of supply sources •Synergy effect Nowadays, the execution of transnational strategies requires logistics managers to control a number of performance criteria, such as processing time, after-sales service, or price. Therefore, it is now believed that firms compete amongst each other with entire supply chains, rather than prices or costs. Hence effective logistics management in a transnational corporation yields competitive advantage [21]. In Poland in the period 2004–2018, i.e., since the country’s accession to the European Union, Polish firms have adopted various forms of internationalization, from export to daughter companies (Figure 2). Logistics 2021, 5, x FOR PEER REVIEW 7 of 17 Nowadays, the execution of transnational strategies requires logistics managers to control a number of performance criteria, such as processing time, after-sales service, or price. Therefore, it is now believed that firms compete amongst each other with entire supply chains, rather than prices or costs. Hence effective logistics management in a transnational corporation yields competitive advantage [21]. In Poland in the period 2004–2018, i.e., since the country’s accession to the European Union, Polish firms have adopted various forms of internationalization, from export to daughter companies (Figure 2). Figure 2. Internationalization of Polish firms. As a result, by the end of 2018 over eighty percent of these enterprises had adopted various forms of internationalization. From 2000 to 2018, the structure of exports and imports saw a major diversification, both within the EU and in the Middle East, China, North and South America, Australia, Japan and Canada. At the same time, foreign capital participation in the capital structure of Polish firms steadily grew by an average of 28.5% per annum. With regard to point no. 2, the phenomenon of service internationalization in the twenty-first century accompanied the contemporary wave of economic globalization, which also included the logistification of economies. The foundation of service provision is the construction or modernization of the infrastructure of logistics to ensure an uninterrupted flow of material and human resources, information, and finances along the service supply chain. Internationalization as a new logistics paradigm in the service sector requires hybridization of services. It also needs to accommodate the attributes of logistics and those elements of the value chain that lay the foundation for competitive advantage [22]. According to Griffin and Pustay [23], the management of services within international logistics should be based on the following principles: • Capacity planning (CP) • Location planning (LP) • Facilities design (FD) • Operations scheduling (OS) Figure 2. Internationalization of Polish firms. Logistics 2021,5, 5 8 of 19 As a result, by the end of 2018 over eighty percent of these enterprises had adopted various forms of internationalization. From 2000 to 2018, the structure of exports and imports saw a major diversification, both within the EU and in the Middle East, China, North and South America, Australia, Japan and Canada. At the same time, foreign capital participation in the capital structure of Polish firms steadily grew by an average of 28.5% per annum. With regard to point no. 2, the phenomenon of service internationalization in the twenty-first century accompanied the contemporary wave of economic globalization, which also included the logistification of economies. The foundation of service provision is the construction or modernization of the infrastructure of logistics to ensure an uninterrupted flow of material and human resources, information, and finances along the service supply chain. Internationalization as a new logistics paradigm in the service sector requires hybridization of services. It also needs to accommodate the attributes of logistics and those elements of the value chain that lay the foundation for competitive advantage [22]. According to Griffin and Pustay [ 23 ], the management of services within international logistics should be based on the following principles: •Capacity planning (CP) •Location planning (LP) •Facilities design (FD) •Operations scheduling (OS) Scheduling provides the optimal arrangement because it factors in consumer preferences, time zones, jet lag, and aircraft utilization. As studies [ 24 ] have shown, today a particular role is attributed to logistic service providers (LSP), with 73% of service givers and 92% of service takers stating that innovation in service provision markedly increases the effectiveness of logistics. In Poland, logistics and transport services exhibit a steady growth trend, not least because of the significant increase in the number of transport firms between 2000 and 2018. It should be noted that, depending on industry, the cost of transport amounts to between 18% and 65% of overall logistic costs, and the haulage services provided by 34,378 Polish transport firms are at the forefront of the industry in the European Union. In this context, it is worth noting that the sales of logistic, transport and storage services is expected to continue to grow at a forecast rate of 2–3.6% per annum (Figure 3). Logistics 2021, 5, x FOR PEER REVIEW 8 of 17 Scheduling provides the optimal arrangement because it factors in consumer preferences, time zones, jet lag, and aircraft utilization. As studies [24] have shown, today a particular role is attributed to logistic service providers (LSP), with 73% of service givers and 92% of service takers stating that innovation in service provision markedly increases the effectiveness of logistics. In Poland, logistics and transport services exhibit a steady growth trend, not least because of the significant increase in the number of transport firms between 2000 and 2018. It should be noted that, depending on industry, the cost of transport amounts to between 18% and 65% of overall logistic costs, and the haulage services provided by 34,378 Polish transport firms are at the forefront of the industry in the European Union. In this context, it is worth noting that the sales of logistic, transport and storage services is expected to continue to grow at a forecast rate of 2–3.6% per annum (Figure 3). Figure 3. Sales of logistic, transport and storage services in Poland in the period 2005–2018 (PLN m). Source: Author’s own work based on GUS 2018. The high level of logistics services in Poland is due to two reasons. Firstly, in order to deliver these services, firms establish logistics services chains that are characterized by the high participation of the client in the service delivery from sender to recipient. Participation of the client in the process of value creation satisfies the recommendations regarding customer-responsive supply chains, i.e., supply chains that adapt to client needs. According to Peng and Meyer [25], the strength of market-responsive supply chains depends on such factors as: • Agility • Adaptability • Alignment Secondly, Poland has seen the dynamic growth of shared services centres (SSC). There are currently 532 such service centres with participation of foreign capital, owned by 360 investors, and employing 150,000 workers [26]. Interestingly, employment in shared services centres has been steadily growing by 25% per annuum since 2008, and a further increase by 20% per annum is being forecast. The types of SSCs located in Poland are also of interest (Figure 4): 84,501 127,560 190,609 204,890 214,900 245,010 0 50,000 100,000 150,000 200,000 250,000 300,000 2005 2010 2015 2016 2017 2018 Year Sales Figure 3. Sales of logistic, transport and storage services in Poland in the period 2005–2018 (PLN m). Source: Author’s own work based on GUS 2018. Logistics 2021,5, 5 15 of 19 Table 6. Transformed indicators of company logistics activities. No. Group of Industries Industry Sales PLN Total Assets PLN m Average Value of Inventories PLN m Share of Inventories in Assets % Logistics Infrastructure Investments Expenditure Costs of Logistics as % Share of Sales Transport Costs as % Share of Sales 1. Producers Metal industry −2.386 −1.109 −0.697 −1.097 −1.097 −0.289 −0.157 2. Pharmaceutical industry −0.859 −2.379 −0.398 −2.270 −2.270 0.144 0.549 3. Electronics industry 0.088 0.322 0.264 −0.268 −0.268 1.227 0.196 4. Distributors Household electrical goods wholesalers 0.914 0.731 −0.749 0.491 0.491 −0.072 0.902 5. Clothing trading companies 0.639 0.719 1.031 0.629 0.629 0.361 −0.510 6. Foodstuffs trading companies −0.231 0.067 −2.035 0.146 0.146 −0.289 1.255 7. Service providers Telecommunications 0.667 0.586 1.083 0.836 0.836 −0.289 −1.922 8. Transport 0.320 0.380 0.420 0.629 0.629 1.443 −1.216 9. Tourism 0.848 0.683 1.083 0.905 0.905 −2.237 0.902 Logistics 2021,5, 5 16 of 19 Subsequently, the value of q i is computed for each of the investigated firms according to the following formula: qi=s∑ j wjxij −xoj2 where: wj—weight assigned to j-th indicator xij—value of j-th indicator for i-th company xoj—the maximum value of j-th indicator in the sample This parameter is a measure of the extent that the indicators for individual companies deviate from the maximum values in the sample. The q i values for individual industries are shown in Table 7. Table 7. The value of qiparameter for individual industries. No. Group of Industries Industry q Indicator Value 1. Producers Metal industry 2.282 2. Pharmaceutical industry 2.021 3. Electronics industry 1.122 4. Distributors Household electrical goods wholesalers 1.058 5. Clothing trading companies 0.814 6. Foodstuffs trading companies 1.467 7. Service providers Telecommunications 1.598 8. Transport 1.228 9. Tourism 2.035 The LMAI indicator is constructed from coefficients q i through their normalisation, i.e., the rescaling of their values to the range (0, 1) in the following way: LMAI =1−qi qo where: qi—the earlier computed qindicator for i-th company qo—the maximum value of qiindicator in the sample The LMAI values computed as above for individual industries, expressed as percentages, are shown in Table 8. Table 8. LMAI values in Polish industry. No. Group of Industries Industry LMAI Indicator Value 1. Producers Metal industry 0.0% 2. Pharmaceutical industry 11.4% 3. Electronics industry 50.8% 4. Distributors Household electrical goods wholesalers 53.6% 5. Clothing trading companies 64.3% 6. Foodstuffs trading companies 35.7% 7. Service providers Telecommunications 30.0% 8. Transport 46.2% 9. Tourism 10.8% We must explain that the zero value for the metal industry results directly from the last stage of the LMAI computation, i.e., the normalisation step. Logistics 2021,5, 5 17 of 19 As can be seen from the processing, the lowest percentage LMAI indicator of information asymmetry in the producers’ group is observed for the pharmaceutical industry, which can be explained by the fact that this industry uses costly state-of-the-art information technology. In the distributor group, a moderately positive result in terms of information asymmetry is observed for food trading firms. Within the service providers, the lowest values of the LMAI indicators are observed in the tourism and telecommunications industries. These findings, however, cannot be generalized beyond the present case, as they only provide a preview of the indisputably interesting and important phenomenon of information asymmetry in Poland. 5. Conclusions Theoretical considerations and the results of empirical studies support the statement proposed in the hypothesis of this article, namely, modern logistics have a mitigating impact on the effects of market information asymmetry. There is also an obvious need for further research, and for the application of the presented LMAI model in business practice. The studies reported in this article can be evaluated at three levels: 1. Methodology: the choice and characteristics of the elements of logistics used in the LMAI model. 2. The empirical layer: the processing of source data collected from Polish firms in the period 2004–2018. 3. The future: propositions for follow-up research to investigate the role of logistics in reducing the effects of market information asymmetry. 1. The Methodological Layer It should be noted that the methodology presented in this article constitutes the first, at least in Polish literature, attempt to quantify the relationship between logistics processes in a firm and their impact on reducing market information asymmetry. Therefore, with due caution the following conclusions can be formulated: • The operation of transforming de-stimulants into stimulants is justified. This is a classical statistical procedure whereby variables belonging to different domains are expressed as a number of standard deviations from the average. • It was deemed necessary to determine parameters q i , which are the measures showing how much individual indicators divert from maximum values in the sample. • As a result, the LMAI indicator was computed from coefficients q i through their normalization, which enabled the expression of the impact of individual logistics processes on the level of market information asymmetry as percentages. 2. The Empirical Layer As in the case of the methodology, the empirical discussion in this article presents a first, original selection of source data from 255 Polish firms. The data were averaged over the period 2004–2018, during which the systematic, linear growth of logistics activities was observed. The following study results deserve attention: • The model evaluates various components of logistics activities such as sales, company assets, inventories, investments in logistics infrastructure, cost of logistics, and cost of transport. • Recognizing the fact that the study findings will be different depending on the type of business activity, three types of firms were identified: manufacturers, distributors and service providers. • The study covered businesses from nine sectors which are key to Poland’s economy. These include metal processing, pharmaceutical, and electronics industries, household electric goods wholesalers, clothing and foodstuffs traders, telecommunications, and tourism. The study findings clearly show that the reduction in information asymmetry due to logistics is greatest in high technology industries. Logistics 2021,5, 5 18 of 19 3. The Future There are ample possibilities for widening the scope of this research, for example, to include geographic considerations. The present study merely provides a starting point for similar research, and the findings cannot be generalized yet or compared with other studies. Here are some suggestions for future research: • The model can process any number of arbitrarily chosen aspects of logistics activities, such as warehousing and inventory holding costs, costs of supplies, value of turnover, etc. • Depending on the region or country where a firm is based, different demand-sensitive industries can be considered, e.g., the chemical industry, automotive industry, furniture manufacturers, or hospitality industry. • Future studies of this interesting phenomenon could also consider different levels of economic development in selected regions of the world. Funding: This research received no external funding. Institutional Review Board Statement: Not applicable. Informed Consent Statement: Not applicable. Data Availability Statement: The data presented in this study are available on request from the corresponding author. Conflicts of Interest: The authors declare no conflict of interest. References 1. Fabbe-Costes, N.; Rouquet, A. (Eds.) 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