Search results

This study aims to develop a performance evaluation model for Facebook (FB) marketing campaigns (FBMCs) for a franchised hotel, distinguish four quadrants based on efficiency and customer attention and suggest improvements for inefficient FBMCs based on the slack value analysis.

The paper applied the elaboration likelihood model to select three inputs (text, picture and color) and three outputs (number of people reached; reactions, comments and shares; and clicks on post) based on the literature and expert opinions to assess 60 FBMCs for hotels through data envelopment analysis and a robustness test. The four-quadrant analysis (benchmark, improvements in efficiency and customer attention and fade-out) provides suggestions for underperforming FBMCs.

The results indicate that the efficiency of the greeting FBMCs is better than that of the event and promotion FBMCs. The projection of input value analysis showed that an average of 50 words, one picture and six colors is the benchmark of FBMCs.

Sixty FBMCs for the same franchised hotel were examined. Further research could extend this model to different hotels for generalization.

The findings suggest that developing shorter text lengths, concise photos and colors of greeting messages on FB could be efficient for FBMCs.

This paper contributes in assessing the performance of FBMCs to identify the benchmark FBMCs with the higher efficiency and more customer attention for a franchised hotel.

The purpose of this study is threefold: to use an innovative metafrontier‐to‐data‐envelopment analysis (MDEA) model incorporating multiple outputs and inputs – including the item revenue, gross profit, food costs, time‐driven labor costs, and other operating expenses (OOEs) – to distinguish four quadrants based on efficiency and profit to offer different strategies to the restaurateur under study; to compare the proficiency levels of the different meal categories of the à la carte and combo set menus using the metatechnology ratio (MTR) via the MDEA; and to use slack‐based analyses with simulation to improve the financial performance of a teppanyaki‐style restaurant.

Six months of point of sale (POS) data are obtained from a teppanyaki‐style restaurant. The proposed inputs are categorized into total food costs, total labor cost, the number of processes, and OOEs. Two outputs (total revenue and gross profit) are used to assess the efficiency of the menu items. The MTR is used to differentiate the proficiency level of the heterogeneous meal categories and to create four quadrants based on the efficiency index and financial performance.

The MTR is lower for the combo set category than for the à la carte category. Four quadrants are obtained based on the efficiency and financial performance to provide further menu suggestions. The MDEA analysis yields menu suggestions that could enhance the overall efficiency and profitability of the menu items. A simulation using these two models is conducted and shows that the restaurant profitability would be 22 percent greater using the MDEA than using the menu engineering model.

Because there are no publicly listed teppanyaki‐style restaurants in Taiwan and it is difficult to find the same menu in different restaurants, this study consists of only a single restaurant, and the results may not be generalizable to other types of restaurants.

This paper contributes to menu analysis by establishing an efficiency index and using financial performance as criteria for determining which menu items to improve in a teppanyaki‐style restaurant. The MTR of the metafrontier model can differentiate the proficiency level of the heterogeneous categories, such as à la carte and combo set menus. This paper offers empirical results pertaining to the classification of menu items and describes a slack‐based analysis for improving menu items.

The purpose of this paper is to examine influential factors on branded app adoption from the perspectives of brand relationship and consumption values. Thus a research model integrating consumer-brand relationship literature and the theory of consumption values is developed.

Using the survey approach, 245 participants were recruited from several app market forums and app fan communities. The banking apps issued by three large banks in Taiwan were used in the research.

The findings support the research model and confirm that brand relationship in terms of brand attachment and brand identification, and perceived overall consumption values are influencing factors in branded app adoption.

The research advances the understanding of the effect of brand relationship on branded app use behavior and the functional and non-functional value components pertaining to branded apps.

Little research has investigated if brand-consumer relationship and consumption values can sustain and continually impact consumers’ choice in mobile apps.