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This article reports on the unusual phenomenon of aggressive competition from cottage firms encountered by multinationals and large local firms in the developing‐country environment. It analyses the conditions that enabled cottage firms to compete aggressively in five industries in India, and how large firms dealt with such competition. It discusses how such competition is likely to vary with industry characteristics. It also discusses the implications of such competition for the strategies of multinationals.

Purpose – Revisiting Fornell et al.'s (1996) seminal study, this chapter looks at the evidence for observed and unobserved heterogeneity within data underlying the American customer satisfaction index (ACSI) model. Examining data for two specific industries (utilities and hotels) reveals only modest differences. However, we suppose that unobserved heterogeneity critically affects the results. These insights provide the basis for shaping further differentiated ACSI model analyses and more precise interpretations.

Methodology/approach – This study applies the partial least squares (PLS) path modeling method and uses empirical data to estimate and compare the ACSI model results on the aggregate and industry-specific data levels. In addition, the finite mixture PLS path modeling (FIMIX-PLS) method is employed to further examine across industry similarities and within industry differences.

Findings – This research uncovers unobserved heterogeneity that guides forming three segments of customers within each industry. The major segment in each industry represents customers that are fairly loyal (i.e., neither disloyal nor extremely loyal) while the other two smaller segments are not as similar across the two industries. Our study identifies substantial differences across these segments within each industry. An importance-performance map analysis illustrates these differences and provides the basis for managerial implications.

Originality/value of the chapter – The unobserved heterogeneity revealed within industries in a given country (i.e., the United States of America) underlines the need to be open to differences within populations, beyond the observed heterogeneity across distinct groups or cultures, and the need to reconsider reporting requirements in academic research.

This study aims to develop a parsimonious model to estimate US aggregate hotel industry revenue using domestic trips, consumer confidence index, international inbound trips, personal consumption expenditure and number of hotel rooms as predictor variables. Additionally, the study applied the model in six sub-segments of the hotel industry – luxury, upper upscale, upscale, upper midscale, midscale and economy.

Using monthly aggregate data from the past 22 years, the study adopted the auto-regressive distribute lags (ARDL) approach in developing the estimation model. Unit root analysis and cointegration test were further utilized. The model showed significant utility in accurately estimating aggregate hotel industry and sub-segment revenue.

All predictor variables except number of rooms showed significant positive influences on aggregate hotel industry revenue. Substantial variations were noted regarding estimating sub-segment revenue. Consumer confidence index positively affected all sub-segment revenues, except for upper upscale hotels. Inbound trips by international tourists and personal consumption expenditure positively influenced revenue for all sub-segments but economy hotels. Domestic trips by US residents added significant explanatory power to only upper upscale, upscale and economy hotel revenue. Number of hotel rooms only had significant negative effect on luxury and upper upscale hotel sub-segment revenues.

Hotel operators can make marketing and operating decisions regarding pricing, inventory allocation and strategic management based on the revenue estimation models specific to their segments.

It is the first study that adopted the ARDL bound approach and analyzed the predictive capacity of macroeconomic variables on aggregate hotel industry and sub-segment revenue.

To determine the status of internet and e‐commerce adoption by the Taiwan semiconductor industry, the research is designed to help government and enterprise in formulating strategic plans and making resource allocation decisions.

Using the three‐level model of internet commerce adoption (MICA), a survey of 287 companies and web sites was designed. Semiconductor firms were placed into five categories: integrated circuit (IC) design, manufacturing, packaging, IC testing, and peripheral device manufacturing.

The MICA model shows the internet adoption ratio for semiconductor firms as 82.6 percent, significantly higher than the electronics and electrical machinery industry sector (56.5 percent). The IC manufacturing and packaging segment are in the processing stage, the final stage of development for the MICA model. One‐third of the IC testing industry segment falls into the provision stage, and 36.1 percent web sites are in the processing stage. The IC design and peripherals industrial segments are located in the provision stage.

The IC manufacturing segment is conducting more financial transactions than the other segments – a result that matches earlier research showing that larger companies are most likely to implement e‐business applications. Many enterprises in the industry are lagging with the adoption of the internet indicating a need for education and training.

This benchmark study provides a framework for evaluating the internet adoption status of semiconductor and other high technology firms. The MICA model is demonstrated to be suitable for evaluating the different stages of internet adoption.

Internal capital markets of diversified firms have been associated with inefficient allocation of investment funds across divisions, leading to value losses. Utilizing a sample of diversified firms that adopted or eliminated Residual Income (RI) plans between 1990 and 2009, we show that adoptions of these plans mitigate investment distortions and lead to value gains. Following the adoption of RI plans, diversified firms start allocating investment funds based on growth opportunities of their divisions. RI plan adopters lower their divisional investment levels, especially in segments with below-average growth opportunities. The overall investment allocation efficiency improves, and the diversification discount diminishes after the adoption of RI plans. However, RI plans appear to be used only as temporary tools for assessing corporate performance. The plans are adopted primarily by firms expected to immediately generate plan bonuses for management, and they are frequently eliminated by firms with bad accounting performance and low managerial bonuses. The study contributes to the literature on organizational efficiency, internal capital markets, and on the importance of measures based on economic profits or RI.

The purpose of this paper is to identify the sources of variation in firm performance. This is one of the cornerstones of strategy research, i.e. the relative importance of industry and firm-level effects on firm performance. Multilevel analysis is well suited to analyze variance in performance when the data are hierarchically structured (industry segments consist of firms, firms operate within the context of industry segments). The Belgian industry studied is a service industry that consists of about 25 electrical wholesalers. Data were collected from 20 firms during the period 1998–2003 from responses to a questionnaire sent to all the firms in the market. The sample in the data set covers more than 95 percent of the market (in sales), as the missing firms were just fringe competitors. The results show that firm effects explain most of the variance in four performance variables. That bears out the importance of each firm having its own specific, idiosyncratic resources and competences. The explanatory power of firm effects varies by about 30–40 percent while the intra-industry effect explains around 10 percent of the variance. Even though firm effects are dominant, intra-industry effects explain a significant portion of the variance in firm-level performance. The firm effect is smaller than in previous studies. The firm effect varies across the performance measures: firm effects are higher for returns on assets than for profit margins. The industry segment effect (or intra-industry effect) is more independent of the dependent variable. The industry segment effect is in line with previous studies on the strategic group effect. Top managers should carefully choose and monitor the intra-industry domain they are in.

This chapter focuses on the application of segment reporting under IFRS 8 in the context of the airline industry. It analyses the airlines’ disclosures related to segment reporting considering 11 aspects of segment reporting in the regional and global context. Observations reveal that reporting of segmental disclosures in the airline industry is diverse at different levels. In this regard, the following conclusions were drawn: (1) the nature of segments reported by the airlines is diverse due to methods adopted in preparation of operating segments; (2) factors such as internal reporting system, and nature of business used to identify the airline’s reportable segments were stated by most airlines; (3) types of products and services from which each reportable segment derives its revenues were stated by all airlines; (4) proportion of total revenues represented by separately reportable segments exceeds 75% of the revenue rule of IFRS 8; (5) most segmental performance measures are non-IFRS and diverse; (6) a limited number of airlines use dual reporting currency in segment reporting; (7) most airlines reported segment assets and liabilities for each reportable segment; (8) most airlines reported between 6 and 10 income and expense items in segment reporting; (9) segmental cash flow information is reported by one airline; (10) in terms of entity-wide disclosures, most airlines reported their revenue from major products and services in the revenue disclosures, most airlines reported their revenues on a geographical basis but few airlines reported their non-current assets on a geographical basis; and (11) more than half of the airlines did not declare the identity of the Chief Operating Decision Maker.

In this paper, we argue that the effect of diversification on performance is not homogeneous across industries, as previously assumed in the literature on diversification in strategy and finance. We provide empirical evidence that some industries are more friendly environments for diversified firms than for specialists, and vice versa. The implications of this qualification for the diversification‐performance relationship are investigated in this study. The results show that the number of specialists in an industry is an important moderator of the diversification‐performance relationship, and it determines the existence of a positive, negative, or curvilinear relationship. Diversification has a more negative impact on performance as the number of specialized firms in the industries in the sample increases. Although we find clear evidence of the curvilinear relationship between diversification and performance frequently found in strategy research, the relationship seems to be the result of not accounting for the relative dominance of diversifiers versus specialists in the industries in the sample.

The paper discusses the new concept of “Multinational Investment Projects” (MIPs) and its application in the context of international business operations in China. The petrochemical industry in China is used as the industrial context in which we investigate the interplay between the Chinese government, which encourages growth and investment activities in the sector, and the multinational petrochemical firms competing for global market share in this sector.

The paper investigates the nature of the petrochemical value chain and the investment activities in all of its segments. Using an originally created database of the top 180 MIPs in the petrochemical industry in China and additional context information the business environment in China, the paper reviews the investment strategies of multinational petrochemical corporations, and discusses their strategic choices for mode of entry in China, geographic location and location within the value chain.

The overview of MIPs in the Chinese petrochemical industry confirms the theoretical expectations of the critical impact of Chinese Government policies. The paper explains the emerging shape of international competition in this sector of the Chinese economy.

The main contributions of this paper are the new conceptual framework for analysis of the drivers for strategic investment choices, the assembly of a database with the top 180 MIPs in the petrochemical industry in China, and the analysis of the relationships between the regional endowments, concentration of value‐chain activities and location choices by multinational firms from different countries of origin. The results demonstrate the factors that drive growth in a knowledge‐, technology‐ and capital‐intensive sector.

The purpose of this paper is to investigate the impact of demand uncertainty on inventory turnover performance through empirical modeling. In particular the authors use the inaccuracy of quarterly sales forecasts as a proxy for demand uncertainty and study its impact on firm-level inventory turnover ratios.

The authors use regression analysis to study the effect of various measures on inventory performance. The authors use a sample financial data for 304 publicly listed US retail firms for the 25-year period from 1985 to 2009.

Controlling for the effects of retail segments and year, it is found that inventory turnover is negatively correlated with mean absolute percentage error of quarterly sales forecasts and gross margin and positively correlated with capital intensity and sales surprise. These four variables explain 73.7 percent of the variation across firms and over time and 93.4 percent of the within-firm variation in the data.

In addition to conducting an empirical investigation for the sources of variation in a major operational metric, the results in this study can also be used to benchmark a retailer’s inventory performance against its competitors.

The authors develop a new proxy to measure the demand uncertainty that a firm faces and show that this measure may help to explain the variation in inventory performance.