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Previous research in the area of distributor performance proposed different scales, mostly in western, developed country context. These studies also lacked the consideration of dynamic interaction between variables, which determine the distributor’s performance. This paper proposes a composite Distributor Performance Index (DPI) to evaluate distributors’ performance based on at the “Enables” and “Results”, taking a system dynamics approach. The model results have been discussed and validated, in business marketing channel. The context of this study is India, an emerging market.

This chapter starts with the phenomenon of CRM systems being sometimes more considered as a burden than a support by salespeople. The main argument is that CRM tools do barely fit the needs of salespeople as their functions, most of all, are administrative, which leads to a resistance for using them.

The author shows how this kind of shortcomings are manifested in “real-life” operations and finds out that much of the problems seem to be due to the very architecture of extant CRM systems. Indeed, creative offerings and business development imply advanced cognitive processes for which there are no functions in traditional CRM tools.

Therefore, the core part of the chapter leads to a discussion on how genuine supportive CRM systems architecture should be designed. The sales process is made of three phases beyond the administration one, namely, a sense-making, a sense-giving, and a sense-acting phase. An adequate architectural design would take into consideration functions that support the whole process, which also includes informative links and a much more visual design to process information instantly.

The purpose of this paper is to examine the widespread of property sellers choosing to sell by themselves or through an estate agent, what characterises them and the reason for their choice. In addition the paper contains comparisons of the gap between sales price and asking price between the sales methods and satisfaction with the sales process. This study is the first study of these phenomena carried out in Norway.

The data used for this study was obtained from a national survey including 1,649 house sellers. A logistic regression analysis is used to analyse the impact of household’s characteristics on the sales method.

The main findings of this study are that 83 per cent of the house sellers used an estate agent through the whole sales process and differences in the choices are related to urbanisation, age and education. The most important reason for preferring a real estate broker is that doing the sale on your own is considered too much work. Conversely, the most important reason for doing the sale on your own is that estate agents are too expensive. Those selling without an estate agent were more satisfied and the gap between sales price and asking price was smaller than for those selling through a real estate broker.

Issues concerning competition within the market for estate agents should be central topics for property management. Property sellers selling their property by themselves are an important contribution to increase the competition in the market for estate agents. This issue has not been on the agenda in Norway, or in Europe, in the same way as in the USA. This is probably due to the complexity in the legislation and strict laws within property sales in Central and Southern Europe. However, in Norway, UK and in the Nordic countries, the legal system is not complicated. It is rather the lockout of private individuals from the housing web sites and the fact that the property sellers are not familiar with this kind of transaction that has prevented property sellers to sell their house by themselves. Today Norway is one of few countries with a booming housing market, which also has increased the commission for estate agents. From 2010 private individuals got access to advertise their house on the housing web sites in Norway. These have influenced the focus on alternative sales methods.

The purpose of this paper is to mine competitive intelligence in social media to find the market insight by comparing consumer opinions and sales performance of a business and one of its competitors by analyzing the public social media data.

An exploratory test using a multiple case study approach was used to compare two competing smartphone manufacturers. Opinion mining and sentiment analysis are conducted first, followed by further validation of results using statistical analysis. A total of 229,948 tweets mentioning the iPhone6 or the GalaxyS5 have been collected for four months following the release of the iPhone6; these have been analyzed using natural language processing, lexicon-based sentiment analysis, and purchase intention classification.

The analysis showed that social media data contain competitive intelligence. The volume of tweets revealed a significant gap between the market leader and one follower; the purchase intention data also reflected this gap, but to a less pronounced extent. In addition, the authors assessed whether social opinion could explain the sales performance gap between the competitors, and found that the social opinion gap was similar to the shipment gap.

This study compared the social media opinion and the shipment gap between two rival smart phones. A business can take the consumers’ opinions toward not only its own product but also toward the product of competitors through social media analytics. Furthermore, the business can predict market sales performance and estimate the gap with competing products. As a result, decision makers can adjust the market strategy rapidly and compensate the weakness contrasting with the rivals as well.

This paper’s main contribution is to demonstrat the competitive intelligence via the consumer opinion mining of social media data. Researchers, business analysts, and practitioners can adopt this method of social media analysis to achieve their objectives and to implement practical procedures for data collection, spam elimination, machine learning classification, sentiment analysis, feature categorization, and result visualization.

The aim of this paper is to investigate CEO succession in China's state‐owned enterprises (SOE) from within intra‐industry labor market. One hypothesis looks at the proportion of SOEs in the industry which will be negatively associated with the likelihood of intra‐firm succession. Another proposition claims the performance gap between SOEs and the industry average level is positively related to the likelihood of intra‐firm succession.

Secondary source data on 79 CEO successions and descriptive company measures were obtained. Background variables such as ROA and employee number were collected from the Tianjin Statistical Yearbook. Pearson and logistic regression coefficients provided tests of hypotheses.

The hypotheses are strongly supported given all measures of performance. The likelihood of intra‐firm succession is negatively associated with the proportion of SOEs in a particular industry. The lower the performance of SOEs behind the industry average level, the greater the likelihood of intra‐firm succession.

The sample size used is moderate. Even though Tianjin is a large industrial center, generalizations to all of China may be limited.

The results support the overall argument that firms within a gradualist economic transition environment in China will tend to choose an internal CEO succession when firms have a limited qualified managerial supply outside the organization. Future research examining the CEO successor in both SOEs and non‐SOEs will provide a more complete picture of organization management with transitional economies evolving into the largest world‐leading economies.

The data base is unique. The paper looks at the business activities and management processes of China's SOEs for the purpose of understanding the way leadership develops; and the organizational effect it has on top management succession. The research not only contributes to the succession literature but also enables managers and investors to better understand the practice of top management succession in Chinese SOEs.

Scholars recognize that international marketing effectiveness requires adapting to cultural values, and at the same time, paradoxically, acknowledge the possibility of cultural convergence. The purpose of this paper is to take the context of Puerto Rico as a US territory to reconcile these two propositions by analyzing culture and gender’s influence on apparel purchase.

Via multiple regression analysis, the study considers seasonality as a factor of apparel purchase patterns, developing a consumer behavior model for the apparel industry.

Results confirm that culture influences purchase behavior, an influence moderated by gender. Additionally, they show that seasons and special occasions are strong predictors of apparel purchase patterns.

The findings assert the claims of cultural convergence, yet preserve the notion that cultural values are reflected in patterns of consumer behavior in the case of apparel.

The study develops highly explanatory models indicating that Puerto Rico expenditure reflects cultural patterns of special occasions, but overshoots expectations for its US counterpart.

The results show that Puerto Rico has appropriated several US cultural aspects (e.g. special holidays), which are expressed differently as reflected by apparel purchase behavior, supporting the notion that Puerto Rico should be treated as an international market. The study demonstrates that cross-cultural studies may be robust in absence of available Hofstede’s dimensions for a country.

Applications powered by artificial intelligence (AI) and machine learning (ML) have become a crucial factor for success in modern sales organizations. This chapter investigates how Salesforce achieves scalable AI for businesses of all sizes and explores sales applications of AI and machine learning that are most common across industries. It is divided into three sections. The first section gives an introduction to AI and machine learning. The second section shows how data and automated machine learning models provide the foundation for AI applications and explains how Salesforce achieves scalable AI and machine learning for business applications. The third section demonstrates how AI applications impact the modern sales organization and the work of sales representatives. AI does not replace humans; it allows sales organizations to better engage with prospects and customers. Sales representatives using AI outperform their counterparts that rely purely on traditional methods.

The case study outlines the strategic, marketing, and branding challenges faced by Gap, a brand within the Gap Inc. house of brands. The case contains a summary of Gap's history, which illustrates the driving forces behind Gap's previous growth, its status as an American iconic brand, and its struggle to stay relevant. This sets the stage for Gap's rebranding exercise, which included an attempt at changing their iconic logo. This case provides students with the opportunity to learn about brand life cycles and the implications of a logo change for brand equity, brand associations, and brand positioning.

This research is based on published sources.

The case can be used in courses in strategic brand management, retailing, fashion marketing, marketing communication, or corporate communication at the graduate or advanced undergraduate level. The case will be particularly useful for those who already understand branding and consumer behavior, but who may not have learned anything about rebranding or strategic brand management. It is not suitable for undergraduates who have not studied branding at all.

In the competitive global market, firms have to keep profit from innovation activities. A firm makes profits by offering products or services at a lower cost than its competitors or by offering differentiated products at premium prices that more than compensate for the extra cost of differentiation. The IC Package and Testing technology industries were the first high technological industry to build in Taiwan. The Package and Testing industries in Taiwan adopted competitive innovation activities to become stronger. In our study, we want to know how innovation activities influence a firm operating in the IC Package and Testing industries. Our study used a questionnaire and Likert five‐point scale to survey the innovation activities, customer and feedback in innovation performance in the IC Package and Testing industry. The wafer level chip size packing technology in our study indicates the innovation activities. Because we need to compare the difference between the wafer level chip size packing technology and wire bonding technology to recognize innovation and how the innovator and customer were influenced. Our conclusions are described below: (1) When the innovator adopts innovation activities that can be maintained using experiments and knowledge, using machine and decision variables more quickly will produce success; (2) Innovators should adopt innovation activities that focus on customers that use knowledge and experimentation, training time and cost. If an innovation forces customers to spend much time and cost to learn new technology or applications, the innovation will not be adopted; (3) Innovators that create innovation performance higher than his customers must also consider the impact upon their customers. We have to remind innovator to focus on why their customers have a different level of evolution in the same innovation activities.

This paper aims to examine the customer-based and supplier-based trade credit gaps for USA firms from 1970 to 2020.

The authors' study examines USA companies from 1970 to 2020. The authors begin with an analysis of the trends in aggregate working capital, the capital's components and the trade credit gaps. Various regression models are used to estimate the impacts of identified firm characteristics and unidentified sources on customer-based and supplier-based trade credit gaps over time. The authors then decompose the impacts of firm characteristics to further understand whether changing firm characteristics and/or changing sensitivity to firm characteristics drive the variation in trade credit gaps.

There is a gradual reduction in the customer-based trade credit gap and a substantial expansion in the supplier-based trade credit gap. Though identified firm characteristics have dominant impacts on observed trade credit gaps, there is evidence of the effects of time and unobservable factors. The main source of changes in customer-based and supplier-based trade credit gaps lies in changes in sensitivity to firm characteristics. In addition, the authors find that firm age is the factor with the largest average effect on both trade credit gaps when examining the full sample period. However, different firm characteristics appear to be the key driver of variations in trade credit gaps over time and across the two types of trade credit gaps. The authors also find that financial distress has the least impact on both customer-based and supplier-based trade gaps. There are variations in the firm characteristics with the largest impacts when evaluating decade-long evaluation periods.

To the authors' knowledge, this is the first paper to examine the customer-based and supplier-based trade credit gaps. The connection between trade credit and the trade credit's corresponding inventory (INV) component extends prior literature on the joint management of trade credit and INV. The authors analyze both identified firm characteristics and unidentified sources in the search for explanations of the trade credit gaps. Furthermore, the authors' study explores the channels through which firm characteristics affect different types of trade credit gaps. The authors' findings help identify relevant and irrelevant risk factors of corporate working capital policy.