Digital economy has grown rapidly so that the new business area called 'Internet business' has been dramatically extended as time goes on. However, in the case of Internet business, market shares of individual companies seem to fluctuate very extremely. Thus marketing managers who operate the Internet sites have seriously observed the competition structure of the Internet business market and carefully analyzed the competitors' behavior in order to achieve their own business goals in the market. The newly created Internet business might differ from the offline ones in management styles, because it has totally different business circumstances when compared with the existing offline businesses. Thus, there should be a lot of researches for finding the solutions about what the features of Internet business are and how the management style of those Internet business companies should be changed. Most marketing literatures related to the Internet business have focused on individual business markets. Specifically, many researchers have studied the Internet portal sites and the Internet shopping mall sites, which are the most general forms of Internet business. On the other hand, this study focuses on the entire Internet business industry to understand the competitive circumstance of online market. This approach makes it possible not only to have a broader view to comprehend overall e-business industry, but also to understand the differences in competition structures among Internet business markets. We used time-series data of Internet connection rates by consumers as the basic data to figure out the competition patterns in the Internet business markets. Specifically, the data for this research was obtained from one of Internet ranking sites, 'Fian'. The Internet business ranking data is obtained based on web surfing record of some pre-selected sample group where the possibility of double-count for page-views is controlled by method of same IP check. The ranking site offers several data which are very useful for comparison and analysis of competitive sites. The Fian site divides the Internet business areas into 34 area and offers market shares of big 5 sites which are on high rank in each category daily. We collected the daily market share data about Internet sites on each area from April 22, 2008 to August 5, 2008, where some errors of data was found and 30 business area data were finally used for our research after the data purification. This study performed several empirical analyses in focusing on market shares of each site to understand the competition among sites in Internet business of Korea. We tried to perform more statistically precise analysis for looking into business fields with similar competitive structures by applying the cluster analysis to the data. The research results are as follows. First, the leading sites in each area were classified into three groups based on averages and standard deviations of daily market shares. The first group includes the sites with the lowest market shares, which give more increased convenience to consumers by offering the Internet sites as complimentary services for existing offline services. The second group includes sites with medium level of market shares, where the site users are limited to specific small group. The third group includes sites with the highest market shares, which usually require online registration in advance and have difficulty in switching to another site. Second, we analyzed the second place sites in each business area because it may help us understand the competitive power of the strongest competitor against the leading site. The second place sites in each business area were classified into four groups based on averages and standard deviations of daily market shares. The four groups are the sites showing consistent inferiority compared to the leading sites, the sites with relatively high volatility and medium level of shares, the sites with relatively low volatility and medium level of shares, the sites with relatively low volatility and high level of shares whose gaps are not big compared to the leading sites. Except 'web agency' area, these second place sites show relatively stable shares below 0.1 point of standard deviation. Third, we also classified the types of relative strength between leading sites and the second place sites by applying the cluster analysis to the gap values of market shares between two sites. They were also classified into four groups, the sites with the relatively lowest gaps even though the values of standard deviation are various, the sites with under the average level of gaps, the sites with over the average level of gaps, the sites with the relatively higher gaps and lower volatility. Then we also found that while the areas with relatively bigger gap values usually have smaller standard deviation values, the areas with very small differences between the first and the second sites have a wider range of standard deviation values. The practical and theoretical implications of this study are as follows. First, the result of this study might provide the current market participants with the useful information to understand the competitive circumstance of the market and build the effective new business strategy for the market success. Also it might be useful to help new potential companies find a new business area and set up successful competitive strategies. Second, it might help Internet marketing researchers take a macro view of the overall Internet market so that make possible to begin the new studies on overall Internet market beyond individual Internet market studies.
Customers often experience waiting for buying service. Managing customers' waiting time is important for service providers since customers who are dissatisfied with waiting, secede from a service place at last. Not a few studies have been done to solve waiting time problem and improve customers' waiting experience. Hui & Tse(1996) identify evaluation factors in customers' behavioral mechanism as customers wait. That is, customers experience perceived waiting time, waiting acceptability and emotional response to the wait when they wait. Since customers evaluate the wait using these factors, service provider should manage these factors in order to minimize customers' dissatisfaction. Therefore, this study explores that evaluation factors of waiting are influenced by customers' situational and experiential characteristics, which include customer loyalty, transaction importance for customer and waiting expectation level. Those situational and experiential characteristics are usually given to service providers so they can't control these at waiting point. The major findings derived from two exploratory studies can be summarized as follows. First, according to the result from the study 1 (restaurant setting), customers' transaction importance has the greatest positive influence on waiting experience. The results show restaurant service provider could prevent customers' separation effectively through strategies which raise customers' transaction importance, like giving special coupons for important events. Second, in study 2 (amusement part setting) customer loyalty has large positive impact on waiting experience as well as transaction importance. This results show that service provider could minimize customers' dissatisfaction using strategies which raise customer loyalty continuously. This results show customer perceives waiting experience differently according to characteristics of service place and service itself. Therefore, service provider should grasp the unique customers' situational and experiential characters for each service and service place. It could provide an effective strategy for waiting time management. Third, the study finds transaction importance and waiting expectation level have direct influence customers' waiting experience as independent variables, while existing studies treated them as moderators. Customer loyalty which has not been incorporated in previous waiting time research is known to affect waiting experience. It suggests that marketing strategy which builds up customer loyalty for long period of time is also quite effective, compared to short term tactics to help customers endure waiting time. Fourth, this study reveals the importance of actual waiting time along with perceived waiting time. So far most studies only focus on customers' perceived waiting time. Especially, this study incorporates the concept of patient limit on waiting time to investigate effect of actual waiting time. The results show that there were various responses to the wait depending on how actual waiting time exceeds individual's patent limit on waiting time or not, even though customers wait about the same period of time. Finally, using structural equation model, conceptual path between behavioral responses is verified. As customer perceives waiting time, then she decides whether she can endure it or not, and then her emotional response occurs. This result are somewhat different from Hui & Tse(1996)'s study. The study also includes theoretical contributions as well as practical implications.
Global challenges such as the corona pandemic, climate change and the war-on-tech ensure that the demand who the technologies of the future develops and monitors prominently for will be on the agenda. Development of, and applications in, agrifood, biotech, high-tech, medtech, quantum, AI and photonics are the basis of the future earning capacity of the Netherlands and contribute to solving societal challenges, close to home and worldwide. To be like the Netherlands and Europe a strategic position in the to obtain knowledge and innovation chain, and with it our autonomy in relation to from China and the United States insurance, clear choices are needed. Brainport Eindhoven: Building on Philips' knowledge base, there is create an innovative ecosystem where more than 7,000 companies in the High-tech Systems & Materials (HTSM) collaborate on new technologies, future earning potential and international value chains. Nearly 20,000 private R&D employees work in 5 regional high-end campuses and for companies such as ASML, NXP, DAF, Prodrive Technologies, Lightyear and many others. Brainport Eindhoven has a internationally leading position in the field of system engineering, semicon, micro and nanoelectronics, AI, integrated photonics and additive manufacturing. What is being developed in Brainport leads to the growth of the manufacturing industry far beyond the region thanks to chain cooperation between large companies and SMEs. South-Holland: The South Holland ecosystem includes companies as KPN, Shell, DSM and Janssen Pharmaceutical, large and innovative SMEs and leading educational and knowledge institutions that have more than Invest €3.3 billion in R&D. Bearing Cores are formed by the top campuses of Leiden and Delft, good for more than 40,000 innovative jobs, the port-industrial complex (logistics & energy), the manufacturing industry cluster on maritime and aerospace and the horticultural cluster in the Westland. South Holland trains thematically key technologies such as biotech, quantum technology and AI. Twente: The green, technological top region of Twente has a long tradition of collaboration in triple helix bandage. Technological innovations from Twente offer worldwide solutions for the large social issues. Work is in progress to key technologies such as AI, photonics, robotics and nanotechnology. New technology is applied in sectors such as medtech, the manufacturing industry, agriculture and circular value chains, such as textiles and construction. Being for Twente start-ups and SMEs of great importance to the jobs of tomorrow. Connect these companies technology from Twente with knowledge regions and OEMs, at home and abroad. Wageningen in FoodValley: Wageningen Campus is a global agri-food magnet for startups and corporates by the national accelerator StartLife and student incubator StartHub. FoodvalleyNL also connects with an ambitious 2030 programme, the versatile ecosystem regional, national and international - including through the WEF European food innovation hub. The campus offers guests and the 3,000 private R&D put in an interesting programming science, innovation and social dialogue around the challenges in agro production, food processing, biobased/circular, climate and biodiversity. The Netherlands succeeded in industrializing in logistics countries, but it is striving for sustainable growth by creating an innovative ecosystem through a regional industry-academic research model. In particular, the Brainport Cluster, centered on the high-tech industry, pursues regional innovation and is opening a new horizon for existing industry-academic models. Brainport is a state-of-the-art forward base that leads the innovation ecosystem of Dutch manufacturing. The history of ports in the Netherlands is transforming from a logistics-oriented port symbolized by Rotterdam into a "port of digital knowledge" centered on Brainport. On the basis of this, it can be seen that the industry-academic cluster model linking the central government's vision to create an innovative ecosystem and the specialized industry in the region serves as the biggest stepping stone. The Netherlands' innovation policy is expected to be more faithful to its role as Europe's "digital gateway" through regional development centered on the innovation cluster ecosystem and investment in job creation and new industries.
Asia-Pacific Journal of Business Venturing and Entrepreneurship
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v.19
no.1
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pp.75-91
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2024
Recently, global business environment is changing dramatically along with the acceleration of technological innovation amid the war, climatic change, and geopolitical instability. Accordingly, it is difficult to predict or plan for the future as the volatility, complexity, ambiguity, and uncertainty of the industrial ecosystem continue to increase. Therefore, organizations are undergoing inevitable restructuring in accordance with their survival strategy, for instance, removing marginal businesses or firing. Accordingly, office workers are seeking a startup as an alternative for their continuous economic activity amid rising anxiety factors that make them think they would lose their jobs unintentionally. Here, this study is aimed to verify through what paths office workers' self-determination influences the process of converting to a startup. For this study, an online survey was carried out, and 310 respondents' valid data were analyzed through SPSS and AMOS. To sum up the results, first, office workers' self-determination did not have significant effects on entrepreneurial intention. However, it was confirmed that self-determination had positive (+) effects on innovativeness and perception of the startup support system. This result shows that their psychology works to prepare step by step by accumulating innovative experiences and increasing perception of the startup support system from a long-term life path perspective rather than challenging startups right way. Second, innovativeness is found to have positive (+) effects on entrepreneurial intention. Also, perception of the startup support system had positive (+) effects on entrepreneurial intention. This implies that when considering startups, they are highly aware of the government's various startup support systems. Third, innovativeness is found to have positive (+) effects on perception of the startup support system. It is judged that perception of the startup support system is valid for prospective founders to exhibit their innovativeness and realize new ideas. Fourth, it was confirmed that innovativeness and perception of the startup support system mediated correlation between self-determination and entrepreneurial intention, and perception of the startup support system mediated correlation between innovativeness and entrepreneurial intention, which shows that it is a crucial factor in entrepreneurial intention. Although previous studies related to startups deal with students mostly, this study targets office workers who form a great part in economic activities, which makes it academically valuable in terms of being differentiated from others and extending the scope of research. Also, when we consider the fact that the motivation for self-determination alone fails to stimulate entrepreneurial intention and the complete mediation of innovativeness and the startup support system, it has great implications in practical aspects such as the government's human and material support systems. In the selection and analysis of samples, this study exhibits a limitation that the problem of common method bias is not completely resolved. Also, additional definitive research is needed on whether entrepreneurial intention is formed and converted into startup behavior. Academically and practically, this study deals with the relationship between humans' psychological motives and startups which has not been handled sufficiently in previous studies. The conversion of office workers to startups is expected to have effects on individuals' economic stability and the state's job creation; therefore, it needs to be investigated continuously for its great value.
Personalized services directly and indirectly acquire personal data, in part, to provide customers with higher-value services that are specifically context-relevant (such as place and time). Information technologies continue to mature and develop, providing greatly improved performance. Sensory networks and intelligent software can now obtain context data, and that is the cornerstone for providing personalized, context-specific services. Yet, the danger of overflowing personal information is increasing because the data retrieved by the sensors usually contains privacy information. Various technical characteristics of context-aware applications have more troubling implications for information privacy. In parallel with increasing use of context for service personalization, information privacy concerns have also increased such as an unrestricted availability of context information. Those privacy concerns are consistently regarded as a critical issue facing context-aware personalized service success. The entire field of information privacy is growing as an important area of research, with many new definitions and terminologies, because of a need for a better understanding of information privacy concepts. Especially, it requires that the factors of information privacy should be revised according to the characteristics of new technologies. However, previous information privacy factors of context-aware applications have at least two shortcomings. First, there has been little overview of the technology characteristics of context-aware computing. Existing studies have only focused on a small subset of the technical characteristics of context-aware computing. Therefore, there has not been a mutually exclusive set of factors that uniquely and completely describe information privacy on context-aware applications. Second, user survey has been widely used to identify factors of information privacy in most studies despite the limitation of users' knowledge and experiences about context-aware computing technology. To date, since context-aware services have not been widely deployed on a commercial scale yet, only very few people have prior experiences with context-aware personalized services. It is difficult to build users' knowledge about context-aware technology even by increasing their understanding in various ways: scenarios, pictures, flash animation, etc. Nevertheless, conducting a survey, assuming that the participants have sufficient experience or understanding about the technologies shown in the survey, may not be absolutely valid. Moreover, some surveys are based solely on simplifying and hence unrealistic assumptions (e.g., they only consider location information as a context data). A better understanding of information privacy concern in context-aware personalized services is highly needed. Hence, the purpose of this paper is to identify a generic set of factors for elemental information privacy concern in context-aware personalized services and to develop a rank-order list of information privacy concern factors. We consider overall technology characteristics to establish a mutually exclusive set of factors. A Delphi survey, a rigorous data collection method, was deployed to obtain a reliable opinion from the experts and to produce a rank-order list. It, therefore, lends itself well to obtaining a set of universal factors of information privacy concern and its priority. An international panel of researchers and practitioners who have the expertise in privacy and context-aware system fields were involved in our research. Delphi rounds formatting will faithfully follow the procedure for the Delphi study proposed by Okoli and Pawlowski. This will involve three general rounds: (1) brainstorming for important factors; (2) narrowing down the original list to the most important ones; and (3) ranking the list of important factors. For this round only, experts were treated as individuals, not panels. Adapted from Okoli and Pawlowski, we outlined the process of administrating the study. We performed three rounds. In the first and second rounds of the Delphi questionnaire, we gathered a set of exclusive factors for information privacy concern in context-aware personalized services. The respondents were asked to provide at least five main factors for the most appropriate understanding of the information privacy concern in the first round. To do so, some of the main factors found in the literature were presented to the participants. The second round of the questionnaire discussed the main factor provided in the first round, fleshed out with relevant sub-factors. Respondents were then requested to evaluate each sub factor's suitability against the corresponding main factors to determine the final sub-factors from the candidate factors. The sub-factors were found from the literature survey. Final factors selected by over 50% of experts. In the third round, a list of factors with corresponding questions was provided, and the respondents were requested to assess the importance of each main factor and its corresponding sub factors. Finally, we calculated the mean rank of each item to make a final result. While analyzing the data, we focused on group consensus rather than individual insistence. To do so, a concordance analysis, which measures the consistency of the experts' responses over successive rounds of the Delphi, was adopted during the survey process. As a result, experts reported that context data collection and high identifiable level of identical data are the most important factor in the main factors and sub factors, respectively. Additional important sub-factors included diverse types of context data collected, tracking and recording functionalities, and embedded and disappeared sensor devices. The average score of each factor is very useful for future context-aware personalized service development in the view of the information privacy. The final factors have the following differences comparing to those proposed in other studies. First, the concern factors differ from existing studies, which are based on privacy issues that may occur during the lifecycle of acquired user information. However, our study helped to clarify these sometimes vague issues by determining which privacy concern issues are viable based on specific technical characteristics in context-aware personalized services. Since a context-aware service differs in its technical characteristics compared to other services, we selected specific characteristics that had a higher potential to increase user's privacy concerns. Secondly, this study considered privacy issues in terms of service delivery and display that were almost overlooked in existing studies by introducing IPOS as the factor division. Lastly, in each factor, it correlated the level of importance with professionals' opinions as to what extent users have privacy concerns. The reason that it did not select the traditional method questionnaire at that time is that context-aware personalized service considered the absolute lack in understanding and experience of users with new technology. For understanding users' privacy concerns, professionals in the Delphi questionnaire process selected context data collection, tracking and recording, and sensory network as the most important factors among technological characteristics of context-aware personalized services. In the creation of a context-aware personalized services, this study demonstrates the importance and relevance of determining an optimal methodology, and which technologies and in what sequence are needed, to acquire what types of users' context information. Most studies focus on which services and systems should be provided and developed by utilizing context information on the supposition, along with the development of context-aware technology. However, the results in this study show that, in terms of users' privacy, it is necessary to pay greater attention to the activities that acquire context information. To inspect the results in the evaluation of sub factor, additional studies would be necessary for approaches on reducing users' privacy concerns toward technological characteristics such as highly identifiable level of identical data, diverse types of context data collected, tracking and recording functionality, embedded and disappearing sensor devices. The factor ranked the next highest level of importance after input is a context-aware service delivery that is related to output. The results show that delivery and display showing services to users in a context-aware personalized services toward the anywhere-anytime-any device concept have been regarded as even more important than in previous computing environment. Considering the concern factors to develop context aware personalized services will help to increase service success rate and hopefully user acceptance for those services. Our future work will be to adopt these factors for qualifying context aware service development projects such as u-city development projects in terms of service quality and hence user acceptance.
This study seeks to understand how the choice of a coffee shop is related to a customer's loyalty and which characteristics of a shop influence this choice. It considers large-sized coffee shops brands whose market scale has gradually grown. The users' choice of shop is determined by price, employee service, shop location, and shop atmosphere. The study investigated the effects of these four properties on the brand attitudes of coffee shops. The effects were found to vary depending on users' characteristics. The properties with the largest influence were shop atmosphere and shop location Therefore, the purpose of the study was to examine the properties that could help coffee shops get loyal customers, and the choice properties that could satisfy consumers' desires The study examined consumers' perceptions of shop properties at selection of coffee shop and the difference between perceptual difference and coffee brand in order to investigate customers' desires and needs and to suggest ways that could supply products and service. The research methodology consisted of two parts: normative and empirical research, which includes empirical analysis and statistical analysis. In this study, a statistical analysis of the empirical research was carried out. The study theoretically confirmed the shop choice properties by reviewing previous studies and performed an empirical analysis including cross tabulation based on secondary material. The findings were as follows: First, coffee shop choice properties varied by gender. Price advantage influenced the choice of both men and women; men preferred nearer coffee shops where they could buy coffee easily and more conveniently than women did. The atmosphere of the coffee shop had the greatest influence on both men and women, and shop atmosphere was thought to be the most important for age analysis. In the past, customers selected coffee shops solely to drink coffee. Now, they select the coffee shop according to its interior, menu variety, and atmosphere owing to improved quality and service of coffee shop brands. Second, the prices of the brands did not vary much because the coffee shops were similarly priced. The service was thought to be more important and to elevate service quality so that price and employee service and other properties did not have a great influence on shop choice. However, those working in the farming, forestry, fishery, and livestock industries were more concerned with the price than the shop atmosphere. College and graduate school students were also affected by inexpensive price. Third, shop choice properties varied depending on income. The shop location and shop atmosphere had a greater influence on shop choice. The customers in an income bracket of less than 2 million won selected low-price coffee shops more than those earning 6 million won or more. Therefore, price advantage had no relation with difference in income. The higher income group was not affected by employee service. Fourth, shop choice properties varied depending on place. For instance, customers at Ulsan were the most affected by the price, and the ones at Busan were the least affected. The shop location had the greatest influence among all of the properties. Among the places surveyed, Gwangju had the least influence. The alternate use of space in a coffee shop was thought to be important in all the cities under consideration. The customers at Ulsan were not affected by employee service, and they selected coffee shops according to quality and preference of shop atmosphere. Lastly, the price factor was found to be a little higher than other factors when customers frequently selected brands according to shop properties. Customers at Gwangju reacted to discounts more than those in other cities did, and the former gave less priority to the quality and taste of coffee. Brand preference varied depending on coffee shop location. Customers at Busan selected brands according to the coffee shop location, and those at Ulsan were not influenced by employee kindness and specialty. The implications of this study are that franchise coffee shop businesses should focus on customers rather than aggressive marketing strategies that increase the number of coffee shops. Thus, they should create an environment with a good atmosphere and set up coffee shops in places that customers have good access to. This study has some limitations. First, the respondents were concentrated in metropolitan areas. Secondary data showed that the number of respondents at Seoul was much more than that at Gyeonggi-do. Furthermore, the number of respondents at Gyeonggi-do was much more than those at the six major cities in the nation. Thus, the regional sample was not representative enough of the population. Second, respondents' ratio was used as a measurement scale to test the perception of shop choice properties and brand preference. The difficulties arose when examining the relation between these properties and brand preference, as well as when understanding the difference between groups. Therefore, future research should seek to address some of the shortcomings of this study: If the coffee shops are being expanded to local areas, then a questionnaire survey of consumers at small cities in local areas shall be conducted to collect primary material. In particular, variables of the questionnaire survey shall be measured using Likert scales in order to include perception on shop choice properties, brand preference, and repurchase. Therefore, correlation analysis, multi-regression, and ANOVA shall be used for empirical analysis and to investigate consumers' attitudes and behavior in detail.
In recent years, one of the major reasons for the fierce competition amongst firms is that they strive to increase their own market shares and customer acquisition rate in the same market with similar and apparently undifferentiated products in terms of quality and perceived benefit. Because of this change in recent marketing environment, the differentiated after-sales service and diversified promotion strategies have become more important to gain competitive advantage. Price promotion is the favorite strategy that most retailers use to achieve short-term sales increase, induce consumer's brand switch, in troduce new product into market, and so forth. However, if marketers apply or copy an identical price promotion strategy without considering the characteristic differences in product and consumer preference, it will cause serious problems because discounted price itself could make people skeptical about product quality, and the changes of perceived value might appear differently depending on other factors such as consumer involvement or brand attitude. Previous studies showed that price promotion would certainly increase sales, and the discounted price compared to regular price would enhance the consumer's perceived values. On the other hand, discounted price itself could make people depreciate or skeptical about product quality, and reduce the consumers' positivity bias because consumers might be unsure whether the current price promotion is the retailer's best price offer. Moreover, we cannot say that discounted price absolutely enhances the consumer's perceived values regardless of product category and purchase situations. That is, the factors that affect consumers' value perceptions and buying behavior are so diverse in reality that the results of studies on the same dependent variable come out differently depending on what variable was used or how experiment conditions were designed. Majority of previous researches on the effect of price-comparison advertising have used consumers' buying behavior as dependent variable. In order to figure out consumers' buying behavior theoretically, analysis of value perceptions which influence buying intentions is needed. In addition, they did not combined the independent variables such as brand loyalty and price discount rate together. For this reason, this paper tried to examine the moderating effect of brand loyalty on relationship between the different levels of discounting rate and buyers' value perception. And we provided with theoretical and managerial implications that marketers need to consider such variables as product attributes, brand loyalty, and consumer involvement at the same time, and then establish a differentiated pricing strategy case by case in order to enhance consumer's perceived values properl. Three research concepts were used in our study and each concept based on past researches was defined. The perceived acquisition value in this study was defined as the perceived net gains associated with the products or services acquired. That is, the perceived acquisition value of the product will be positively influenced by the benefits buyers believe they are getting by acquiring and using the product, and negatively influenced by the money given up to acquire the product. And the perceived transaction value was defined as the perception of psychological satisfaction or pleasure obtained from taking advantage of the financial terms of the price deal. Lastly, the brand loyalty was defined as favorable attitude towards a purchased product. Thus, a consumer loyal to a brand has an emotional attachment to the brand or firm. Repeat purchasers continue to buy the same brand even though they do not have an emotional attachment to it. We assumed that if the degree of brand loyalty is high, the perceived acquisition value and the perceived transaction value will increase when higher discount rate is provided. But we found that there are no significant differences in values between two different discount rates as a result of empirical analysis. It means that price reduction did not affect consumer's brand choice significantly because the perceived sacrifice decreased only a little, and customers are satisfied with product's benefits when brand loyalty is high. From the result, we confirmed that consumers with high degree of brand loyalty to a specific product are less sensitive to price change. Thus, using price promotion strategy to merely expect sale increase is not recommendable. Instead of discounting price, marketers need to strengthen consumers' brand loyalty and maintain the skimming strategy. On the contrary, when the degree of brand loyalty is low, the perceived acquisition value and the perceived transaction value decreased significantly when higher discount rate is provided. Generally brands that are considered inferior might be able to draw attention away from the quality of the product by making consumers focus more on the sacrifice component of price. But considering the fact that consumers with low degree of brand loyalty are known to be unsatisfied with product's benefits and have relatively negative brand attitude, bigger price reduction offered in experiment condition of this paper made consumers depreciate product's quality and benefit more and more, and consumer's psychological perceived sacrifice increased while perceived values decreased accordingly. We infer that, in the case of inferior brand, a drastic price-cut or frequent price promotion may increase consumers' uncertainty about overall components of product. Therefore, it appears that reinforcing the augmented product such as after-sale service, delivery and giving credit which is one of the levels consisting of product would be more effective in reality. This will be better rather than competing with product that holds high brand loyalty by reducing sale price. Although this study tried to examine the moderating effect of brand loyalty on relationship between the different levels of discounting rate and buyers' value perception, there are several limitations. This study was conducted in controlled conditions where the high involvement product and two different levels of discount rate were applied. Given the presence of low involvement product, when both pieces of information are available, it is likely that the results we have reported here may have been different. Thus, this research results explain only the specific situation. Second, the sample selected in this study was university students in their twenties, so we cannot say that the results are firmly effective to all generations. Future research that manipulates the level of discount along with the consumer involvement might lead to a more robust understanding of the effects various discount rate. And, we used a cellular phone as a product stimulus, so it would be very interesting to analyze the result when the product stimulus is an intangible product such as service. It could be also valuable to analyze whether the change of perceived value affects consumers' final buying behavior positively or negatively.
Internet commerce has been growing at a rapid pace for the last decade. Many firms try to reach wider consumer markets by adding the Internet channel to the existing traditional channels. Despite the various benefits of the Internet channel, a significant number of firms failed in managing the new type of channel. Previous studies could not cleary explain these conflicting results associated with the Internet channel. One of the major reasons is most of the previous studies conducted analyses under a specific market condition and claimed that as the impact of Internet channel introduction. Therefore, their results are strongly influenced by the specific market settings. However, firms face various market conditions in the real worlddensity and disutility of using the Internet. The purpose of this study is to investigate the impact of various market environments on a firm's optimal channel strategy by employing a flexible game theory model. We capture various market conditions with consumer density and disutility of using the Internet.
shows the channel structures analyzed in this study. Before the Internet channel is introduced, a monopoly manufacturer sells its products through an independent physical store. From this structure, the manufacturer could introduce its own Internet channel (MI). The independent physical store could also introduce its own Internet channel and coordinate it with the existing physical store (RI). An independent Internet retailer such as Amazon could enter this market (II). In this case, two types of independent retailers compete with each other. In this model, consumers are uniformly distributed on the two dimensional space. Consumer heterogeneity is captured by a consumer's geographical location (ci) and his disutility of using the Internet channel (${\delta}_{N_i}$).
shows various market conditions captured by the two consumer heterogeneities.
(a) illustrates a market with symmetric consumer distributions. The model captures explicitly the asymmetric distributions of consumer disutility in a market as well. In a market like that is represented in
(c), the average consumer disutility of using an Internet store is relatively smaller than that of using a physical store. For example, this case represents the market in which 1) the product is suitable for Internet transactions (e.g., books) or 2) the level of E-Commerce readiness is high such as in Denmark or Finland. On the other hand, the average consumer disutility when using an Internet store is relatively greater than that of using a physical store in a market like (b). Countries like Ukraine and Bulgaria, or the market for "experience goods" such as shoes, could be examples of this market condition.
summarizes the various scenarios of consumer distributions analyzed in this study. The range for disutility of using the Internet (${\delta}_{N_i}$) is held constant, while the range of consumer distribution (${\chi}_i$) varies from -25 to 25, from -50 to 50, from -100 to 100, from -150 to 150, and from -200 to 200.
summarizes the analysis results. As the average travel cost in a market decreases while the average disutility of Internet use remains the same, average retail price, total quantity sold, physical store profit, monopoly manufacturer profit, and thus, total channel profit increase. On the other hand, the quantity sold through the Internet and the profit of the Internet store decrease with a decreasing average travel cost relative to the average disutility of Internet use. We find that a channel that has an advantage over the other kind of channel serves a larger portion of the market. In a market with a high average travel cost, in which the Internet store has a relative advantage over the physical store, for example, the Internet store becomes a mass-retailer serving a larger portion of the market. This result implies that the Internet becomes a more significant distribution channel in those markets characterized by greater geographical dispersion of buyers, or as consumers become more proficient in Internet usage. The results indicate that the degree of price discrimination also varies depending on the distribution of consumer disutility in a market. The manufacturer in a market in which the average travel cost is higher than the average disutility of using the Internet has a stronger incentive for price discrimination than the manufacturer in a market where the average travel cost is relatively lower. We also find that the manufacturer has a stronger incentive to maintain a high price level when the average travel cost in a market is relatively low. Additionally, the retail competition effect due to Internet channel introduction strengthens as average travel cost in a market decreases. This result indicates that a manufacturer's channel power relative to that of the independent physical retailer becomes stronger with a decreasing average travel cost. This implication is counter-intuitive, because it is widely believed that the negative impact of Internet channel introduction on a competing physical retailer is more significant in a market like Russia, where consumers are more geographically dispersed, than in a market like Hong Kong, that has a condensed geographic distribution of consumers.