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Companies spend millions on training their sales representatives. Thousands of textbooks have been published; thousands of training videos have been recorded. Hundreds of good pieces of advice and tips for sales representatives have been presented along with hundreds of sales methods and techniques. Probably the largest number of indicators and measures are applied in sales and distribution. On the one hand, this is a result of the fact that sales provide revenue and profit to a company; on the other hand, the concept of management by objectives turns out to be most effective in regional sales teams with reference to sales representatives and methods of performance evaluation. As a result, a whole array of indices has been created which enable the evaluation of sales representatives’ work and make it possible to manage goods distribution in a better way.

The indices presented in this chapter are rooted in the consumer market and are applied most often to this type of market (particularly in relation to fast-moving consumer goods at the level of retail trade). Nevertheless, many of them can be used on other markets (services, means of production) and at other trade levels (wholesale).

Although the values of many indices presented herein are usually calculated by market research agencies and delivered to companies in the form of synthetic results, we have placed the emphasis on the ability to determine them independently, both in descriptive and exemplifying terms. We consider it important to understand the genesis of indices and build the ability to interpret them on that basis. What is significant is that the indices can be interpreted differently; the same index may provide a different assessment of a product’s, brand or company’s position in the market depending on the parameters taken into account. Therefore, we strive to show a certain way of thinking rather than give ready-made recipes and cite ‘proven’ principles. Sales and distribution are dynamic phenomena, and limiting them within the framework of ‘one proper’ interpretation would be an intellectual abuse.

It seems that the Internet boom, which started at the end of the 1990s and finished with the spectacular collapse of the so-called dotcoms, is probably over. We are currently enjoying a period of fast and stable growth. This is manifested by the growing number of both Internet users and companies which – to an ever-increasing extent – use the Internet as a form of communication (both internal and external), promotion, sales etc. Expenditures on Internet advertising are growing continuously and now constitute more than 25% of all advertising expenditure. A natural consequence of this development is the need for the standardisation and organisation of the world of the Internet. These activities will result in a greater awareness of the benefits which this medium provides, increasing the possibilities of its use, and – most importantly – the opportunity to evaluate the return on investments made on the Internet. Nowadays, it is clear that many companies are striving to increase the quality of their activities on the Internet or to improve the effectiveness of such activities. As a consequence, the number of companies that look for indices which would enable the making of more precise and effective decisions in the scope of online operations is growing.

This chapter is dedicated to the phenomenon of the increasing role of the Internet in business, including the scale of its use by Polish and international companies. We present the most commonly used measures of marketing activities on the Internet and in social media. This group includes the indices which make it possible to determine whether a company actually needs a website. Other measures allow for the improvement in the effectiveness of the activity on the Internet, whereas others specify the costs of activities on the Internet and often serve as the basis for settlements between a company and advertising agencies or companies specialising in website design. It is worth emphasising that the Paid, Earned, Shared, Owned (PESO) model, worked out by Don Bartholomew,¹ is the basis for creation and description of indices concerning social media. This model has gained certain popularity in the social media industry. It does not, however, specify how individual indices should be named and calculated. It maps already existing indices and adapts them to specific levels of marketing communication measurement. All the measures indicated by the author of the model have been grouped into five major areas: exposure, engagement, brand awareness, action and recommendations. This model– similarly to all models of performance measurement – inspired by the sales funnel concept, adjusts certain standard indices and proposals of measurements for specific levels. Additionally, the measures are divided into four types, depending on who the owner of the content is: Paid (P) – refers to all forms of paid content; Owned (O) – all websites and web properties controlled by a company or brand; Earned (E) – the contents about a given brand created spontaneously by Internet users; and Shared (S) – the contents shared by Internet users.

Inner city centers not only provide opportunities for shopping, dining, and entertainment, but with their lively atmosphere and other vital attributes, also create attractive destinations for residents and tourists alike. However, inner city retailing, potentially the most important reason to visit an inner city, is facing serious competition from e-commerce and out-of-town shopping malls. Dying inner city centers have become a severe issue in recent years, worldwide. To counteract this devastating trend and ensure the vitality and viability of inner city centers, stakeholders from the public and private sectors regularly join their forces in initiatives to strengthen urban structures. However, academic insights into the contribution of retailing on perceived city attractiveness remain sparse. Relying on an extensive data set that combines survey and observational data, the authors are able to quantify a variety of inner city characteristics, ranging from its store and service provider portfolio to its ambience and accessibility, and measure their association with its perceived attractiveness. They show that a city's portfolio of retail stores is not only related to people's perceptions of the city's overall attractiveness but also perceptions of its ambience. However, not all retail categories contribute the same way; while the presence of clothing stores or booksellers is strongly associated with cities' ambience as well as attractiveness, other retail categories such as optometrists or electronics stores are negatively associated with consumers' inner city perceptions. Importantly, these relationships also depend on the size of the focal city. Based on their results, the authors provide important managerial and societal implications on how to leverage the local retailing environment to improve inner city attractiveness. For example, the results may inform (local) governments on which sectors to subsidize in order to attract those store and service provider categories that benefit inner city attractiveness.

This chapter explores how customer's attributes, shopping behavior, and preferences affect the retail choice in fiercely competitive retail environments of megacities from developing countries. We study how small, family-owned retailers (i.e., nanostores) compete against organized chains from the modern channel (i.e., convenience stores and supermarkets) at different socioeconomic levels in 9 out of 16 boroughs from Mexico City. Primary data were collected using a combination of instruments (i.e., observation, interviews, and surveys) that were applied to relevant stakeholders of the retail footprint where nanostores develop their operations. We analyze the data via statistical tools such as descriptive statistics and independent nonparametric tests to understand the significant factors of the competitive landscape in which nanostores are immersed. We supplement our research methodology by using causal loop diagrams to identify opportunities in the way suppliers, shopkeepers, competitors, and customers interact with each other and new business models for the nanostore supply chains. By breaking down our result analysis into low-, middle-, and high-income areas, we provide insightful recommendations to increase nanostores' survival, improve their operations, and grow them in Mexico City by addressing issues from the supply, store management, and customer service.

Smart card-based E-payment systems are receiving increasing attention as the number of implementations is witnessed on the rise globally. Understanding of user adoption behavior of E-payment systems that employ smart card technology becomes a research area that is of particular value and interest to both IS researchers and professionals. However, research interest focuses mostly on why a smart card-based E-payment system results in a failure or how the system could have grown into a success. This signals the fact that researchers have not had much opportunity to critically review a smart card-based E-payment system that has gained wide support and overcome the hurdle of critical mass adoption. The Octopus in Hong Kong has provided a rare opportunity for investigating smart card-based E-payment system because of its unprecedented success. This research seeks to thoroughly analyze the Octopus from technology adoption behavior perspectives.

Cultural impacts on adoption behavior are one of the key areas that this research posits to investigate. Since the present research is conducted in Hong Kong where a majority of population is Chinese ethnicity and yet is westernized in a number of aspects, assuming that users in Hong Kong are characterized by eastern or western culture is less useful. Explicit cultural characteristics at individual level are tapped into here instead of applying generalization of cultural beliefs to users to more accurately reflect cultural bias. In this vein, the technology acceptance model (TAM) is adapted, extended, and tested for its applicability cross-culturally in Hong Kong on the Octopus. Four cultural dimensions developed by Hofstede are included in this study, namely uncertainty avoidance, masculinity, individualism, and Confucian Dynamism (long-term orientation), to explore their influence on usage behavior through the mediation of perceived usefulness.

TAM is also integrated with the innovation diffusion theory (IDT) to borrow two constructs in relation to innovative characteristics, namely relative advantage and compatibility, in order to enhance the explanatory power of the proposed research model. Besides, the normative accountability of the research model is strengthened by embracing two social influences, namely subjective norm and image. As the last antecedent to perceived usefulness, prior experience serves to bring in the time variation factor to allow level of prior experience to exert both direct and moderating effects on perceived usefulness.

The resulting research model is analyzed by partial least squares (PLS)-based Structural Equation Modeling (SEM) approach. The research findings reveal that all cultural dimensions demonstrate direct effect on perceived usefulness though the influence of uncertainty avoidance is found marginally significant. Other constructs on innovative characteristics and social influences are validated to be significant as hypothesized. Prior experience does indeed significantly moderate the two influences that perceived usefulness receives from relative advantage and compatibility, respectively. The research model has demonstrated convincing explanatory power and so may be employed for further studies in other contexts. In particular, cultural effects play a key role in contributing to the uniqueness of the model, enabling it to be an effective tool to help critically understand increasingly internationalized IS system development and implementation efforts. This research also suggests several practical implications in view of the findings that could better inform managerial decisions for designing, implementing, or promoting smart card-based E-payment system.

This chapter reviews research on the question–behavior effect, the phenomenon that asking questions influences respondents’ behavior. Two distinct research streams, the self-prophecy effect, concerned with socially normative behaviors, and the mere measurement effect, dealing with purchase behaviors without socially normative significance, are identified. Despite the recent attempt at integration, it is argued that there are fundamental differences between the two effects. Distinctions are also drawn between lab-based and field-based mere measurement effects, and between normatively consistent and implicit attitude-driven, normatively inconsistent self-prophecy effects. Key studies, theoretical explanations, and moderators of each effect are discussed, potential unanswered questions and research opportunities are identified, and significant managerial and policy implications are highlighted.

The COVID-19 pandemic had severely impacted global commerce, leading to market closure and travel restrictions. Due to the extreme limitations on shopping and market possibilities, consumers’ buying habits have changed significantly and they are still changing what they buy and how they purchase for everyday necessities. They are trying to shop locally, carefully, and economically. Consumers are buying their stuff from wherever goods are available. Purchasing nonessential items is restricted. Restaurants, tourism, apparel, and furniture are the industries that have been impacted the most. The objective behind this study is to find out the post-COVID-19 effects on consumer buying of essentials from a convenience store over hypermarkets and how consumer behavior will revive postpandemic toward retail shopping. In the study, responses were collected through structured questionnaire to explore the consumer buying behavior for their daily essentials both at convenience stores and hypermarkets. The study reveals that consumers prefer to buy essential commodities/goods of daily needs from convenience store compared to hypermarket due to the risk of being exposed to COVID-19 pandemic and this behavior will change future trend of retail shopping experience. The major limitation of the study is sampling frame. Future studies can replicate this study in different context with different target population. Pertaining to the current ongoing situations of the pandemic, a very high percentage of the respondents would still choose nearby convenience stores over hypermarkets. This study estimates the behavioral change in retail consumers in future; therefore, it suggests retailers adopt innovative marketing strategy in future.