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As more women are now being appointed to senior and top management positions and invited to sit on boards of directors, they are now directly participating in strategic company decision-making. As female directors have been found to provide new ideas, increase company competitiveness, efficiency and performance and bring a greater number of external resources to a company than male directors, this paper aims to put female directors as a variable into the data envelopment analysis (DEA) and statistical models to explore the effect of female directors on operating performances. The DEA first quantified and measured the company efficiencies, after which the statistical model analyzed the correlations between the variables to specifically identify the impact of female decision makers on the operating efficiencies in state-owned and private enterprises.

A novel two-stage, meta-hybrid dynamic DEA was developed to explore Chinese cultural media company efficiencies under optimal input and output resource allocations, after which Tobit Regression was applied to determine the effect of female executives on these efficiencies.

From 2012 to 2016, the overall efficiencies in Chinese state-owned cultural media enterprises were better than in the private cultural media enterprises. The overall technology gaps (TGs) in the state-owned cultural media enterprises were better than in the private cultural media enterprises.

Previous research has tended to focus on the causal relationships between female senior executives and business performances; however, there have been few studies on the relationships between female executives and company performance from an efficiency perspective (optimal resource allocation). This paper, therefore, is the first to develop a novel two-stage, meta-hybrid dynamic DEA to examine Chinese cultural media enterprise efficiencies, and the first to apply Tobit Regression to assess the effect of female executives on those efficiencies.

In the reduction of food waste and the provision of food to the hungry, food banks play critical roles. However, as they are generally run by charitable organisations that are chronically short of human and other resources, their inbound logistics efforts commonly experience difficulties in two key areas: 1) how to organise stocks of donated food, and 2) how to assess the donated items quality and fitness for purpose. To address both these problems, the authors aimed to develop a novel artificial intelligence (AI)-based approach to food quality and warehousing management in food banks.

For diagnosing the quality of donated food items, the authors designed a convolutional neural network (CNN); and to ascertain how best to arrange such items within food banks' available space, reinforcement learning was used.

Testing of the proposed innovative CNN demonstrated its ability to provide consistent, accurate assessments of the quality of five species of donated fruit. The reinforcement-learning approach, as well as being capable of devising effective storage schemes for donated food, required fewer computational resources that some other approaches that have been proposed.

Viewed through the lens of expectation-confirmation theory, which the authors found useful as a framework for research of this kind, the proposed AI-based inbound-logistics techniques exceeded normal expectations and achieved positive disconfirmation.

As well as enabling machines to learn how inbound logistics are handed by human operators, this pioneering study showed that such machines could achieve excellent performance: i.e., that the consistency provided by AI operations could in future dramatically enhance such logistics' quality, in the specific case of food banks.

This paper’s AI-based inbound-logistics approach differs considerably from others, and was found able to effectively manage both food-quality assessments and food-storage decisions more rapidly than its counterparts.

Restaurants’ outdoor signage plays an irreplaceable role in attracting potential diners, as it conveys important functional and symbolic meanings of the businesses. The purpose of this study is to investigate the effect of typographic design elements of outdoor signage on consumers’ perceptions of authenticity. This study also tests the linkage between authenticity and willingness to dine, as well as the moderating effect of frequency of dining in ethnic restaurants on the relationship.

Using a 2 (simplified vs traditional Chinese characters) × 2 (calligraphy vs computer font) × 2 (vertical vs horizontal text flow) between-subject design, the authors did two experiments with 786 Chinese diners. Restaurant authenticity and willingness to dine are dependent variables, and openness to ethnic cuisine is the control variable.

Display characters and text flow significantly affect restaurant authenticity. Furthermore, the results of this study demonstrate that display characters interact with typeface to influence restaurant authenticity. Consumers’ perceived authenticity significantly increases their willingness to dine. The frequency of dining in ethnic restaurants moderates the relationship between restaurant authenticity and willingness to dine.

Ethnic restaurateurs should pay attention to the outdoor signage design, as it affects potential consumers’ authenticity perceptions. Specifically, in Mainland China, traditional Chinese characters and vertical text direction increase potential consumers’ authenticity perceptions.

This study extends the semiotic theory and applies the cue–judgment–behavior model in the hospitality literature. This study also provides new understanding of authenticity by identifying the influence of typographic design on authenticity, which confirms the semiotic theory that certain semiotic cues affect consumers’ judgments.