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Discusses product line change ‐ the process by which a company alters its product offering ‐ and how it is one of the most important kinds of business activity. Suggests that product modification and product elimination decisions be treated together as two amongst a number of alternative courses of action. States that the concern is with the “weak product identification” stage of the product modification/elimination process. Posits that there are a number of key performance dimensions/criteria though some of the approaches in this category are concerned only with identifying weak products. Aims to put forward some empirical evidence with regard to the identification of weak products. Implies, in conclusion, that the study indicates that the identification of weak product activities does not resemble the normative models in this area. Identifies that further research needs to be conducted and that these researches should include performance measures to allow normative conclusions to be drawn, perhaps using company interviews

With the intensification of market competition, there is a growing demand for weak signal identification and evolutionary analysis for enterprise foresight. For decades, many scholars have conducted relevant research. However, the existing research only cuts in from a single angle and lacks a systematic and comprehensive overview. In this paper, the authors summarize the articles related to weak signal recognition and evolutionary analysis, in an attempt to make contributions to relevant research.

The authors develop a systematic overview framework based on the most classical three-dimensional space model of weak signals. Framework comprehensively summarizes the current research insights and knowledge from three dimensions of research field, identification methods and interpretation methods.

The research results show that it is necessary to improve the automation level in the process of weak signal recognition and analysis and transfer valuable human resources to the decision-making stage. In addition, it is necessary to coordinate multiple types of data sources, expand research subfields and optimize weak signal recognition and interpretation methods, with a view to expanding weak signal future research, making theoretical and practical contributions to enterprise foresight, and providing reference for the government to establish weak signal technology monitoring, evaluation and early warning mechanisms.

The authors develop a systematic overview framework based on the most classical three-dimensional space model of weak signals. It comprehensively summarizes the current research insights and knowledge from three dimensions of research field, identification methods and interpretation methods.

Since its introduction by Chari, Kehoe, and McGrattan (2007), Business Cycle Accounting (BCA) exercises have become widespread. Much attention has been devoted to the results of such exercises and to methodological departures from the baseline methodology. Little attention has been paid to identification issues within these classes of models. In this chapter, the authors investigate whether such issues are of concern in the original methodology and in an extension proposed by Šustek (2011) called Monetary Business Cycle Accounting. The authors resort to two types of identification tests in population. One concerns strict identification as theorized by Komunjer and Ng (2011) while the other deals both with strict and weak identification as in Iskrev (2010). Most importantly, the authors explore the extent to which these weak identification problems affect the main economic takeaways and find that the identification deficiencies are not relevant for the standard BCA model. Finally, the authors compute some statistics of interest to practitioners of the BCA methodology.

This paper investigates the semantic association mechanisms of weak demand signals that facilitate innovative product development in terms of conceptual and temporal precedence, despite their inherent ambiguity and uncertainty.

To address this challenge, a domain ontology approach is proposed to construct a customer demand scenario-based framework that eliminates the blind spots in weak demand signal identification. The framework provides a basis for identifying such signals and introduces evaluation indices, such as depth, novelty and association, which are integrated to propose a three-dimensional weak signal recognition model based on domain ontology that outperforms existing research.

Empirical analysis is carried out based on customer comments of new energy vehicles on car platform such as “Auto Home” and “Bitauto”. Results demonstrate that in terms of recognition quantity, the three-dimensional weak demand signal recognition model, based on domain ontology, can accurately identify six demand weak signals. Conversely, the keyword analysis method exhibits a recognition quantity of four weak signals; in terms of recognition quality, the three-dimensional weak demand signal recognition model based on domain ontology can exclude non-demand signals such as “charging technology”, while keyword analysis methods cannot. Overall, the model proposed in this paper has higher sensitivity.

This paper proposes a novel method for identifying weak demand signals that considers the frequency of the signal's novelty, depth and relevance to the target demand. To verify its effectiveness, customer review data for new energy vehicles is used. The results provide a theoretical reference for formulating government policies and identifying weak demand signals for businesses.

This chapter proposes a simple, fairly general, test for global identification of unconditional moment restrictions implied from point-identified conditional moment restrictions. The test is a Hausman-type test based on the Hausdorff distance between an estimator that is consistent even under global identification failure of the unconditional moment restrictions, and an estimator of the identified set of the unconditional moment restrictions. The proposed test has a χ2 limiting distribution and is also able to detect weak identification. Some Monte Carlo experiments show that the proposed test has competitive finite sample properties already for moderate sample sizes.

The authors propose inference methods for endogeneity parameters in linear simultaneous equation models allowing for weak identification and missing instruments. Endogeneity parameters measure the impact of unobserved variables which may be correlated with observed explanatory variables, and play a central role in determining the “bias” associated with endogeneity and measurement errors in structural equations. These results expand, in several ways, the finite-sample theory in Doko Tchatoka and Dufour (2014) for this problem. The latter theory relies on relatively restrictive assumptions, in particular the hypothesis that the reduced form is complete (e.g., contains all the relevant instruments), which is questionable in many practical situations. While the new proposed inference methods retain identification robustness, they also allow the reduced form to be incomplete, for example, due to missing instruments. The authors propose easily applicable inference methods for endogeneity parameters – in particular, two-stage procedures (similar to those in Dufour, 1990). An application to a model of returns to schooling is presented.

This paper aims to empirically analyze the extent to which advertising reception among consumers with a migration background (German-Turks) is influenced by a person’s strength of national identifications with his/her country-of-origin (COO) and with his/her country-of-residence (COR). The focus is on Turkey-sensitive advertisements (ads) of telecommunication service suppliers in Germany because such communication measures are quite common and about three million German-Turks constitute an economically important group.

Measures of COO and COR identification as well as of three ad reception criteria were obtained in a survey of 291 German-Turks and analyzed via moderated regression models.

Strength of COO identification was a significantly positive predictor of the frequency with which participants remembered Turkey-sensitive ads for telecommunication services. Additionally, COO identification related significantly to two criteria that capture facets of attitudes toward such ads. By contrast, COR identification acted partly as a moderator which attenuated links between respondents’ COO identification and two ad reception measures. Nevertheless, German-Turks with a strong COR identification (i.e. “accultured” consumers) were still receptive to Turkey-sensitive telecommunication services ads even if their self-image was simultaneously strongly dependent on their COO. “Alienated” German-Turks who identify neither with their COO nor with their COR were least responsive to ethnic ads.

The research indicates that marketing practitioners should not use uniform communication measures to address migrant consumers with a specific COO but segment this target group further by simultaneously considering their members’ COO and COR identifications.

The contribution of this paper results from the simultaneous inclusion of both COO and COR identifications as factors explaining differences in reactions to communication measures among migrant consumers which share the same COO. Furthermore, the scarcity of empirical work on reactions of German-Turks to ethnomarketing is reduced.

The study seeks to examine two variables of interest to marketers in the area of services advertising, ethnicity and service involvement. The goal of this study is to investigate the relative effectiveness of ethnic‐targeting in services advertising, specifically, Hispanic‐targeted advertising. The purpose of this research is to understand what types of services can benefit from Hispanic‐targeted service advertising and develop practical implications for practitioners trying to spend advertising dollars more efficiently.

The impact of the advertising model's ethnicity on post‐exposure attitude toward high and low involvement service brands was explored.

The results of this quasi‐experimental study suggest that appealing to strong Hispanic identifiers may be highly desirable in terms of creating favorable attitudes toward service brands when advertising low involvement services, where, by definition, the consumer does not engage in intensive decision making and considers few attributes. Since few attributes are evaluated, obvious attributes such as ethnicity can easily influence choice. Finally, the findings of this study suggest that employing Hispanic‐targeted advertising may not be an effective strategy in promoting high‐involvement services since consumers consider more attributes and, therefore, ethnicity does not play a major role.

Of interest to marketers in the area of services advertising, ethnicity and service involvement.

From a distinctiveness theory and elaboration likelihood model (ELM) perspective, this study aims to investigate the determinants, the direct and indirect effects of ethnic identification on brand attachment, brand love and behavioral outcomes. The authors examine two types of products (high- vs low-involvement).

In a survey, participants were randomly assigned to four conditions consisting of two high-involvement (i.e. a smart watch and a car) and two low-involvement (i.e. a soda/soft drink and a shampoo) stimuli. A total of 192 respondents participated in this study; 39% were male, 61% were female and 90% were 18-22 years old.

In line with ELM, the authors offer evidence that ethnic advertising is more effective for low-involvement products targeted at African American consumers. Results also showed that brand attachment partially mediates the effect of ethnic identification with the ad (EthIdenAD) and brand love. In summary, the structural equation modeling (SEM) results support the efficacy of ethnic-targeted ads for developing brand attachment, brand love and behavioral outcomes.

Using ethnically targeted ads to target minority groups may not be sufficient to increase the efficacy of ads. According to distinctiveness theory, African Americans with different levels of ethnic identification will respond differently to ad attitudes, brand attachment, brand love, identification with the model in the ad and varying degrees of belief that the ad was targeted toward them.

This study examines the effect of ethnically targeted advertising on brand love, and behavioral outcomes with the mediation effect of brand attachment and moderation effect of product involvement. The results of this study suggest several theoretical and practical implications for marketing and brand management, including directions for advertising strategy and consumer–brand relationships.

The purpose of this paper is to test the ability of the theory of planned behaviour to predict worker intent towards an employee involvement (EI) programme, and the impact of union identification on workers’ decision making.

Union workers at a small manufacturing company in the Midwestern United States completed two questionnaires. The first questionnaire provided measures of the attitudinal, normative, and behavioural control components of the theory of planned behaviour and the degree to which they identified with their labour union. In the second questionnaire, the same respondents answered questions to measure their intention to support or oppose an employee involvement (EI) programme.

Intentions to support EI were accurately predicted from attitudes, normative support, and perceived behavioural control (0.05 level). Level of union identification moderated the impact of attitudes on intention to support EI for workers that did not identify heavily with the labour union (0.05 level), but did not moderate the effect of normative support on intention for workers who identified heavily with the labour union.

The results indicate that the theory of planned behaviour has the potential to be an effective tool in predicting the behavioural outcomes of union members in the workplace, and that the level of union identification affects decision making. Research is limited by same source methodology and no direct measure of behaviour.

Leaders, labour and management, who intend to implement new programmes, should give strong consideration to how workers’ social cohorts influence their decision making and plan for this contingency when considering programme changes.

The level of union identification influences perception and decision making but has not been considered in models of member decision making. EI research has tended to center on EI as the antecedent to outcomes such as job satisfaction, cooperation, retention, and quality of work life. This paper addresses the role of union identification in support for EI programmes, and uses a well‐established behavioural theory to explain workers’ decision‐making process.