A literature review and future agenda for B2B branding: Challenges of branding in a B2B context

The existing body of research knowledge on brand management has been predominantly derived from business-to-consumer markets, particularly fast moving consumer goods and has only recently started to expand in other contexts. Branding in business-to-business markets has received comparatively little attention in the academic literature due to a belief that industrial buyers are unaffected by the emotional values corresponding to brands. This paper provides a critical discussion of the fragmented literature on business-to-business branding which is organized in five themes: B2B branding benefits; the role of B2B brands in the decision making process; B2B brand architecture; B2B brands as communication enablers and relationship builders; and industrial brand equity. Drawing on the gaps and contradictions in the literature the paper concludes by proposing an agenda for future research.     

Forecasting unstable and nonstationary time series

Many time series are asymptotically unstable and intrinsically nonstationary, i.e. satisfy difference equations with roots greater than one (in modulus) and with time-varying parameters. Models developed by Box–Jenkins solve these problems by imposing on data two transformations: differencing (unit-roots) and exponential (Box–Cox). Owing to the Jensen inequality, these techniques are not optimal for forecasting and sometimes may be arbitrary. This paper develops a method for modeling time series with unstable roots and changing parameters. In particular, the effectiveness of recursive estimators in tracking time-varying unstable parameters is shown with applications to data-sets of Box–Jenkins. The method is useful for forecasting time series with trends and cycles whose pattern changes over time.     

Application capability of e-business, e-business success, and organizational performance: Empirical evidence from China

Previous research efforts suggested that firms' overall e-business success tends to deliver greater organizational performance. However, few researchers examined how a firm leverages e-business investment to gain greater e-business success. Even fewer researchers investigated the different impacts of different levels of e-business success on organizational performance. This paper addresses two questions: (1) what capabilities influence a firms' ability to build e-business success and enjoy greater organizational performance, where firm-level e-business success is measured by e-business service capability and IT-enabled collaborative advantage; and (2) whether the two ways of measuring e-business success result in different impacts on organizational performance? We propose that a firm's application capability of e-business involving systems development and systems usage is positively related to a firm's overall e-business success, thus having a positive impact on organizational performance. We use survey data from 152 Chinese manufacturing firms and their B2B e-business systems participants to test our theoretical hypotheses and proposed model. The findings suggest that both systems development and systems usage have significant and positive impacts on e-business service capability, which in turn leads to greater IT-enabled collaborative advantage. This finding could be translated into the important role of a firm's application capability of e-business on e-business success. It is concluded that the application capability of e-business acts as one of the main mechanisms through which the e-business investment leads to greater e-business success. We also find that IT-enabled collaborative advantage, compared with e-business service capability, has a more significant and greater impact on organizational performance. This study extends prior e-business success research by opening up the ‘black box’ between a firm's e-business investment and its e-business success, and by distinguishing the relative impacts of e-business service capability versus IT-enabled collaborative advantage on organizational performance. Another contribution of this study is that the effect of context factors (firm size, industry, and system duration) in developing country on our proposed model.     

Improving forecasting for telemarketing centers by ARIMA modeling with intervention

In this study we analyze existing and improved methods for forecasting incoming calls to telemarketing centers for the purposes of planning and budgeting. We analyze the use of additive and multiplicative versions of Holt–Winters (HW) exponentially weighted moving average models and compare it to Box–Jenkins (ARIMA) modeling with intervention analysis. We determine the forecasting accuracy of HW and ARIMA models for samples of telemarketing data. Although there is much evidence in recent literature that “simple models” such as Holt–Winters perform as well as or better than more complex models, we find that ARIMA models with intervention analysis perform better for the time series studied.     

Cultural aspect and technological development: a Chinese perspective

This paper explores the cultural characteristics that deter and stimulate the development of a total technology and identifies the significant cultural differences among individuals with strong and weak Chinese cultural inclinations through statistical analysis of the results of an empirical survey.     

Investment choices: Indivisible non-marketable assets and suboptimal solutions

Several investment decisions deal with non-marketable assets. Non-marketable assets are available only to one investor and are often indivisible. This has relevant consequences on investor investment opportunities. Adhering to a mean–variance representation of the investment space and considering a non-marketable asset (divisible or not), we derive some possible investment scenarios an investor may face. Furthermore, we show how a limited ability to gather and process information affects investor portfolio choices. Our results define a set of conditions under which the non-marketable asset represents a good investment and show that, under certain assumptions, the efficient frontier exhibits non-linearities and intervals of discontinuity.     

The R and D/Marketing interface and single informant bias in NPD research: an illustration of a benchmarking case study

Analysing the performance of new product development (NPD) processes requires the reliable assessment of non-documented organizational characteristics. Based on key informant literature we discuss the difficulties of gaining reliable information from respondents and we identify potential sources for heterogeneous perceptions among different respondents. We assume that NPD research may be subject to response biases, if it is based on sole informants only. We apply an existing benchmarking approach for NPD processes in a comprehensive case study in order to illustrate sources and effects of single informant biases. We find that perceptions differ substantially among the individual respondents. In particular, we observe different functional perceptions between respondents from Marketing and Research and Development. The results are consistent with expectations from interface theory. These perceptual differences have a severe impact on the managerial conclusions drawn from benchmarking. There appears to be no single reliable source of information within an organization. Furthermore, variances among informants' assessments should be recognized and regarded as valuable information. It is our recommendation that multiple informants ought to be included in future NPD research and benchmarking studies.     

The impact of incentives on the accuracy of subjects in judgmental forecasting experiments

There is an ongoing debate in the social sciences about whether or not financial incentives are needed in order to obtain good performance from experimental subjects. This debate often extends into the research on judgmental forecasting. Thus, an experiment was conducted to assess the effects of financial incentives on time series forecasting accuracy. There was no evidence that financial incentives impacted forecasting accuracy in stable time series. Financial incentives also had no impact immediately after instabilities occurred and no impact once the trend in the data had fully emerged.     

Long-term recurrence patterns in the late 2000 economic crisis: Evidences from entropy analysis of the Dow Jones index

The depth (4.5% US GDP decline and 9.5% stable unemployment) and duration (more than two years) of the present global economic recession have suggested to many researchers and practitioners to think that it is singular relative to previous recession that occurred in the aftermath of the World War II. It has been argued that the singularity of the late 2000 crises arises from non-precedent components, such as globalization and a dominant financial system equipped with exotic instruments (e.g., derivatives) designed from highly specialized mathematical theories. This paper uses the historic (1928–2010) Dow Jones index analyzed with informational entropy methods to show the presence of recurrent cycles with dominant periods of 4.5 and 22 years. For time series, entropy is a measure of the diversity of patterns for given time scales. In this form, the higher the entropy, the more complex the underlying system dynamics. It is shown that the present economic downturn coincides with the occurrence of a 22-year cycle in the entropy dynamics of the Dow Jones index. It suggests that the crisis is not singular, but its origin can be also explained from recurrent long-term patterns. Implications of the empirical results for the evolution of the late 2000 crisis and the potential aftermath courses of the global economy are discussed.