Search results

This exploratory study examines how promotional effectiveness is determined in small firms and examines decision‐makers attitudes toward promotional performance and measurement. Although it is commonly believed that small business managers rely upon intuitive methods, this study suggests that most small business managers apply some objective measure of effectiveness to their promotional strategies, typically using multiple methods. Evaluation techniques usually center on measures of financial performance and consumer behavior, with some firms relying on employee input for the assessment of promotional performance. The size of the firm and the gender of the decision‐maker account for significant differences in the frequency and type of evaluation methods applied. The majority of small business managers are somewhat satisfied with how well their promotional efforts perform, however, many experience difficulty in determining the impact of their promotions and could benefit from the development of models and techniques designed specifically for use in small firms.

The aim of this paper is to investigate an optimal promotional strategy of intra-category cross-selling on culinary products for the fiercely competitive, fast-moving consumer goods (FMCG) industry.

A linear regression model and a Markov switching autoregressive model is used, that incorporates a retailing demand process to capture a nonlinear structure among promotional budget allocation, and evaluate promotional performance, and optimal promotional frequency within a given time span. Three product categories are applied with 39 months of time-series data from a multinational packaged food company in Taiwan.

The result shows that most previous decisions on promotional budget allocation are non-optimal – most promotional investments were either extended too long or allocated too low in stimulating sales.

This study suggests implications for the brand or category manager in removing such non-optimal promotional policies.

Previous promotional investment is evaluated by comparing the changes in promotional budget allocation. Markov's switching feedback rules are then applied to determine the proper length of equilibrium state with and/or without promotion. Finally, effective decision rules on magnitude, duration, and frequency of intra-category promotional strategy are induced.

Since 2016, organized retailers in Colombia have struggled against a new retail format: Hard-discount stores. This sales channel fulfills essential shopping basket products with consistent low prices. To be competitive and preserve their market position, organized retailers must improve their processes and their pricing decisions. Promotions and discounts have been considered as an effective alternative to compete. This study analyzes the impact of joint prices decisions over the individual and global financial key performance indicators when a collaborative strategy is adopted. Our case study comprises a supermarket chain Colombian retailer and a consumer packaged-goods manufacturer to analyze its supply chain performance. The analysis considers different product categories (food, personal care, and cosmetics) and country regions. The results highlight that benefits are unequally distributed along different echelons and supply chain performance is affected when pricing decisions are made independently.

This study aims to identify and analyse the key determinants influencing customer satisfaction towards online shopping in India.

The literature concerning major attributes of website functionality, perceived usability, perceived usefulness and customer satisfaction in online retailing were reviewed. Data were collected from 365 respondents active in online shopping for examining the constructs. The model was empirically tested using structural equation modelling.

The findings of the study reveal that perceived usefulness and website functionality have a positive impact on customer satisfaction, whereas perceived usability had a significant but negative impact on customer satisfaction.

This research will help online retailers to attract and motivate new customers for online shopping and existing customers to extend it in their daily purchase. Online retailers can improve post purchase satisfaction and eventually increase online customers.

This is one of the preliminary study dealing with customer satisfaction towards online retailing in India. The scale has been extended to include items like satisfaction with cash on delivery mode of payment not included in previous scales. The scale of perceived usefulness has also been deepened by adding time performance, product performance and promotional performance.

The purpose of this paper is to investigate the underlying dimensions of trade show performance in an emerging market context. Firms in industrial and emerging markets typically differ in terms of access to firm level resource endowments. Such differences make attempts to generalize the trade show performance dimensions proposed for industrialized country exhibitors to emerging market exhibitors problematic. This motivates the need for understanding the dimensionality of trade show performance in an emerging market context.

Data obtained from firms that partake in an emerging market trade show that takes place in an emerging market are used to investigate the dimensionality of trade show performance. By subjecting several trade show performance items into principal component analysis, a multidimensional performance construct, applicable to emerging market exhibitors, is introduced.

The empirical findings show that trade show performance, in an emerging market context, is multidimensional. The findings suggest that emerging market exhibitors tend to utilize trade shows somewhat differently from their industrialized market counterparts.

The findings imply the need for exhibit managers in emerging markets to set multiple objectives for trade show participations. The findings also suggest that exhibit managers need to staff the trade show booth with individuals possessing different sets of expertise.

The paper clarifies the dimensionality of trade show performance in the context of emerging markets and sheds light on the tactical and the strategic roles that trade show participations play in emerging markets.

In the public sector, Training and Experience (T & E) exams assess prior experience and are one of the most often used methods for selecting job applicants. This study uses a KSA approach, where raters judge the quality of job relevant prior experience, not its duration or quantity. It was hypothesized that an additional rater and a consensus meeting between raters would increase reliability and validity.

T & E and supervisory ratings were obtained over a 12-year period for 166 candidates seeking promotion to a budget analyst position. Validity was measured by the correlation between T & E scores and supervisory ratings. Consensus was required only for T & E scores differing by a specific amount (hybrid consensus).

Intraclass reliability was 0.73, 0.84, and 0.95 in the one-rater, two-rater, and hybrid consensus conditions with each coefficient greater than the next (p < 0.05) showing the benefit of multiple raters and consensus for reliability. Validity was significant at 0.21, 0.26, and 0.251 for each rating condition, respectively (two-tail test; p < 0.01). Validity was greater in the two-rater condition than in the one-rater condition (one-tail test; p < 0.05). Consensus did not improve validity beyond that of two raters. For consensus T & Es (n=76), two raters improved validity (one-tail test; p < 0.05), moving from 0.112 to 0.231 but not reliability; consensus improved reliability (two-tail test; p < 0.05) but not validity.

There has been a vacuum in T & E research for close to 20 years. Validity data are difficult to obtain but critical for meta-analysis. T & Es showed validity. Use of two raters improved validity but consensus did not increase the gain.

Two of the primary growth strategies for Major League Soccer (MLS) have been team expansion and the construction of soccer-specific stadiums. Therefore, the purpose of this paper is to determine the relationship between these factors and game-specific MLS spectator attendance.

Two multiple regression models, one using multi-level mixed effects linear regression and another using interval regression, were developed to explain the variation in attendance utilizing the two factors of interest along with other control factors that have been identified as attendance determinants in previous literature. Game-specific data were collected for five MLS seasons, 2007-2011.

The two regression models explained approximately 40 percent of the variation in spectator attendance and the results showed that expansion teams and soccer-specific stadiums were significantly related to attendance. However, the effect of soccer-specific stadiums was minimized due to the extreme success of the Seattle Sounders in drawing about twice as many fans as the next highest drawing franchise, yet playing in an American football stadium.

While many of the standard factors such as the presence of holidays and novelty players, competition from other professional teams, and day of week, competition from other professional teams; team quality failed to show significance. Expansion teams drew better than incumbent teams and the impact from soccer-specific stadia is weak given the success of the Seattle franchise (and possibly negative when excluding Seattle). Censoring of the dependent variable had a discernible impact on many of the attendance factors.

These findings may be useful to managers of MLS and their teams along with other professional teams and/or leagues that are investigating the use of either team expansion or the construction of new facilities to increase spectator attendance.

This is the first study to investigate the relationship between expansion and new stadium construction in MLS over multiple years. The results indicate that MLS’s decision to use team expansion and the construction of soccer-specific stadiums has been beneficial with respect to spectator attendance.

The main purpose of this research is to investigate the influence of promotional inputs presented to salespeople, such as continuing medical education (CME) sponsorship and drug samples, on adaptive selling and sales performance.

This study used a mixed-methods approach. First, depth interviews were done and this was followed by a survey on 247 pharmaceutical executives in India. Data analysis was done using AMOS, Process Macro and floodlight analysis.

Results showed that CME sponsorship and drug samples drove adaptive selling and sales performance positively. Additionally, results reveal that CME program sponsorship negatively moderated the adaptive selling–sales performance relationship; free drug samples too negatively moderated this relationship.

Firms may hire salespersons with high customer orientation and adaptive selling and train them hone these further. The present research also crucially suggests that pharma firms may allocate CME sponsorship and drug samples to salespeople low on adaptive selling.

This could be the first study, to the best of the authors’ knowledge, that uses promotional inputs (such as CME sponsorship and drug samples) as an antecedent to adaptive selling and sales performance. Moreover, this is the only research that has tested CME sponsorships and drug samples as moderators to customer orientation–adaptive selling and adaptive selling–sales performance.

A common complaint about shopping malls is the “sameness” of them. Despite this, shopping mall groups are increasingly using group branding as the basis for promotional activities, emphasising the security for the customer of knowing that they will receive the same level of mix, no matter which “branch” is shopped at. This research examines the effectiveness of group versus local promotional activities, with the premise that level of local market dominance will impact on the effectiveness of both promotional types. The two key performance indicators of sales and foot traffic were used to measure effectiveness. Findings suggest that promotional type and level of market dominance have significant effects on sales and traffic. Managerial implications are offered, along with suggestions for future research extending this study to other retail groups.

In this study, three models were empirically compared, the DeLone and McLean model, the Seddon model and the Modified Seddon model, by measuring the impact of a business intelligence system (BIS) in companies in Peru. After that, the mediators and dependent constructs were analysed to determine if they were behaving properly (a good level of variance explanation and significant relations with others constructs). The study used a sample of 104 users of the BIS, from companies in several important economic sectors, in a quasi-voluntary context and with six constructs: information quality, system quality, service quality, system dependence (system use), user satisfaction and perceived usefulness (individual impact).

To interpret the results, the authors used structural equations. The idea was to look for the best fit and explanations for the outcomes. The main difference in these models is that the DeLone and McLean model considers system dependence (system use) as a part of information system success, but in the Seddon model, it is a consequence of it.

The Seddon model seems to show the best fit and explanation for the outcomes. After that, a review of the system use construct was realised, because of its limited variance explained and the few significant relations with other constructs, to improve its explanation power in future research.

It is estimated that the sample includes more than 15 per cent of all the companies that use a BISs in Peru, so the size of the sample is adequate, but it is not entirely random and therefore limits the generalizability of outcomes. Besides that, a sample size that is bigger could be better for the sake of making a more detailed analysis, permitting the use of some items with less power, or the use of another statistical procedure for structural equations such as the Asymptotical Distribution Free, permitting a more detailed analysis (Hair et al., 2006).

Business intelligence (BI), one of the most important components of information systems (IS), is playing a very relevant role in business in this time of high competition, high amounts of data and new technology. Currently, companies feel pressured to respond quickly to change and complicated conditions in the market, needing to make the correct tactical, operational and strategic decisions (Chugh and Grandhi, 2013). BI is one of the most important drivers of the decade (Gartner, 2013). Big companies of IS are creating special units specialised in BI, helping companies become more efficient and effective in daily operations.