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Restaurants in South Africa have a notoriously high failure rate. This study aims to identify drivers of restaurant efficiency in South Africa.

A stochastic cost frontier function with three inputs (i.e. labour, food and beverage and materials) and one output as the total revenue is specified and used to estimate restaurant efficiency. An extensive data collection using primary and secondary sources enabled the researcher to gather data from 42 restaurants, for the year 2016, on a variety of parameters.

The findings show that on average restaurants were operating at 77%, with the most and least efficient restaurants operating at a 97 and a 43% efficiency level, respectively. From the study, it is clear that two structural drivers, namely, “location” and “operation type”, and two executional drivers, namely, “restaurant type” and “revenue per available seat hour”, significantly impacted (p < 0.05) on restaurant efficiency in South Africa.

Despite the importance of this study, it is not free of limitations. First, the research was based on efficiency drivers for restaurants situated in a specific South African province. Caution is therefore required when generalising the findings of this study to restaurants in other geographic areas, as a replication of this study in other geographic areas might reveal varying levels of efficiency. Second, the measurement of restaurant efficiency was limited to five efficiency drivers. Even though these efficiency drivers were included in other studies as well, there could be other relevant efficiency drivers that are likely to influence restaurant efficiency.

To improve efficiency, restaurateurs should first concentrate on the drivers that can be changed in the short term (executional drivers) and then later focus on the drivers that require long-term planning (structural drivers). Restaurateurs should understand the use of RevPASH strategies to manipulate demand during peak and off-peak periods. Furthermore, restaurants should be able to change the table mix to optimise table configuration. Changing a restaurant’s table configuration during peak times increases efficiency.

This paper is a first attempt to identify drivers of operational efficiency using a stochastic approach in the restaurant industry in South Africa. As restaurants in South Africa have a high failure rate, the results could assist restaurateurs in managing more successful entities.

Due to increased health concerns, restaurant customers rely more on credible cues that indirectly represent health-related credence quality. To comprehensively understand the dynamics between credence cues and restaurant delivery with different infection risks, this study aims to investigate changes in cue utilization during the pandemic.

Data on delivery sales, brand and review rating between 2019 and the first half of 2020 were obtained from Meituan. Fixed-effects estimation was used to investigate 579,858 restaurant observations across 338 cities in China.

Health concerns significantly increased the use of restaurant delivery and the increased delivery sales remained steady even after infection risk was reduced. However, cue utilization in restaurant delivery substantially changed depending on inflection risk. In the pandemic-spreading period, the sales effect of the brand increased while that of review rating decreased. The decreased effect of review rating was recovered in the pandemic-flattening period, whereas the abnormal brand effect continued only when branded restaurants had a high rating.

The findings demonstrate the selective and contextual nature of cue utilization in the restaurant delivery setting. These characteristics are also manifested in a health crisis from a credence cue perspective.

The findings demonstrate the selective and contextual nature of cue utilization in the restaurant delivery setting. These characteristics are also manifested in a health crisis from a credence cue perspective. Further, this study re-conceptualizes credence quality and cues, considering their roles in risk management. The findings help develop risk management strategies based on customers’ usage patterns of credence cues in health crises.

The dynamics between credence cues and restaurant delivery has not been comprehensively investigated, especially when infection risk changes. This study delivers theoretical and practical contributions about how to use credence cues in the restaurant business amid health crises.

Restaurants are characterised by predictable, seasonal factors and unpredictable, individual customer demand, which make it difficult for restaurateurs to attain efficiency. A combination of these two factors, macro-predictability and micro-uncertainty, produces economic risks, which make it difficult for restaurants to attain operational efficiency. The purpose of this study is to identify factors impacting restaurant efficiency in South Africa.

By using primary and secondary sources, data were collected from 16 different types of restaurants in South Africa, for the period 2012-2016, on a variety of parameters. A two-stage empirical analysis was carried out, which involved the estimation of operational efficiencies during the first stage by using data envelopment analysis (DEA) and determination of factors impacting restaurant performance in South Africa during the second stage by using two-way random-effects generalised least squares and Tobit regression models.

The results clearly show that the ability of restaurants to succeed will not be determined by their size but by their type, location and revenue per available seat. While the study finds various factors impacting on operational efficiency, the survival of restaurants in South Africa seem to be determined by cost efficiency, which brings in better market performance through lowering cost of sales.

The results have implications for restaurant managers in that if they want to improve cost efficiency, they must manage restaurant capacity and customer demand in a way that maximises revenue. To stimulate demand during periods of low demand, management could consider strategies that attract more customers or encourage upselling, whereas during periods of high demand, management may consider raising prices or reducing meal durations. The results indicate that DEA is a useful tool to identify factors impacting restaurant efficiency and could enhance the service data and revenue management with regards to restaurant efficiency in South Africa.

To the best of the author’s knowledge, this paper is the first that attempts to identify factors impacting restaurant efficiency in South Africa by using DEA. The findings could enhance the service data and revenue management with regards to restaurant efficiency in South Africa.

This paper aims to present an extension of price sensitive measurement (PSM) combined with activity-based costing (ABC) for supporting activity-based pricing approaches in the small and medium-sized restaurants.

The joint model of PSM and ABC is applied to the fixed menu pricing analysis of a typical medium-small Italian restaurant.

The outcomes confirm the potential of the activity-based pricing approach for supporting pricing decision-making in the small and medium-sized restaurants. However, the complexity of the model for these contexts suggests testing simplified versions of ABC, proposed for other sectors, to exploit integration with PSM. Further, the authors find evidence of the need to further investigate the role of informal conditions, characterizing small-medium enterprises, which may play for the successful implementation of the approach proposed.

There is no analysis using the suggested approach for supporting menu pricing in medium-small restaurants. This case study contributes to the literature on activity-based pricing for small and medium-sized restaurants, based on the ABC approaches.

This paper aims to investigate actual tourist customer visiting behavior with behavioral data from Google Popular Times to evaluate the extent that such an online source is useful to better understand, analyze and predict tourist consumer behaviors.

Following six hypotheses on tourist behavior, a purpose-built software tool was developed, pre-tested, and then used to obtain a large-scale data sample of 20,000 time periods for 198 restaurants. Both bi-variate linear regression and correlation analyzes were used for hypothesis testing.

Support was established for the hypotheses, through an analysis of customer reviews, timing effects, the number of pictures uploaded and price segment information provided by tourists to a given restaurant. Also, a relationship to average duration time was found to be positive. The findings demonstrate that data provided through Google Popular Times matches theoretical and logical assumptions to a high degree. Thus, the data source is potentially powerful for providing valuable information to stakeholders (e.g. researchers, managers and tourists).

This paper is the first to both conceptually and empirically demonstrate the practicality and value of Google Popular Times to better understand, analyze and predict tourist consumer behaviors. Value is thereby provided by the potential for this approach to offer insights based behavioral data. Importantly, until now such an approach to gathering and analyzing this volume of actual customer data was previously considered far less practical in terms of time and expense.

本研究旨在用谷歌热门时段(Google Popular Times)的行为数据来探讨游客的实际访问行为, 以评估此种线上资源对理解、分析和预测游客消费行为的实用程度。

基于对游客访问行为的六个假设, 本研究开发并前测一种专用软件工具, 用其收集198家餐厅中20,000个时间段的大规模数据样本。双变量线性回归(bi-variate linear regression)和相关性分析(correlation analyzes)均用于检验假设。

研究结果支持本文假设, 包含顾客评论数量、时间影响、图片数量以及价格区间等资讯對特定餐厅游客平均数量之預測; 同时亦发现与平均持续时间的正向关系。研究结果证明, 谷歌热门时段所提供的数据很大程度上符合理论与逻辑假设。因此, 其具备潜在强大功能, 能为利害关系人（如研究者, 管理者, 游客）提供高价值的资讯。

本研究是第一个从概念与实证上证明谷歌热门时段的实用性和价值, 进而深入理解、分析和预测游客消费行为。此方式透过行为数据来提供深入的见解并创造价值; 重要的是, 在此之前, 这种收集与分析大量实际顾客数据的方法被认为缺乏时间与成本效益。

El presente documento tiene como objetivo investigar las conductas de visita de los clientes turísticos reales con datos de comportamiento de Tiempos populares de Google (Google Popular Times) para evaluar el grado en que dicha fuente online es útil para comprender, analizar y predecir mejor las conductas de los consumidores turísticos.

Siguiendo seis hipótesis sobre el comportamiento de los clientes turístico visitante, se desarrolló una herramienta de software especialmente diseñada, probada con anterioridad y posteriormente se utilizó para obtener una muestra de datos a gran escala de 20.000 períodos de tiempo para 198 restaurantes. Se utilizaron tanto la regresión lineal bi-variante como los análisis de correlación para probar las hipótesis.

Se apoya la hipótesis que incluyen la cantidad de comentarios de los clientes, los efectos de tiempo, el número de imágenes y la información del segmento de precios sobre la cantidad de turistas que visitan un restaurante determinado en promedio. Además, se encuentra una relación positiva con el tiempo de duración promedio. Los hallazgos demuestran que los datos proporcionados a través de Google Popular Times coinciden en alto grado con las suposiciones teóricas y lógicas. Por lo tanto, la fuente de datos es potencialmente eficaz para proporcionar información valiosa a los interesados (por ejemplo, investigadores, administradores, turistas).

Este ensayo es el primero que demuestra conceptual y empíricamente la practicidad y el valor de Google Popular Times para entender, analizar y predecir mejor el comportamiento del consumidor turístico. Por lo tanto, el valor es proporcionado por el potencial de este enfoque para ofrecer datos de comportamiento basados en la comprensión. Es importante señalar que hasta ahora ese enfoque para reunir y analizar ese volumen de datos reales sobre los clientes se consideraba menos práctico en términos de tiempo y gastos.

Notes that good service delivery has come a long way from “smile training”, but many managers are left wondering whether they should put emphasis on the “hard” or the “soft” aspects of service. There is no doubt that “soft” issues are key and many successful service companies stress the importance of developing customer‐friendly values, a positive environment and interpersonal skills to match. Remarks that “hard” aspects are important too and include process alignment, customer surveys, benchmarking standards and capacity management. The ability to handle times when something goes wrong demonstrates the interplay of “hard” and “soft”, service delivery necessitates a complex blend of “hard” and “soft” approaches.

This paper examines conceptual links between facilities and hospitality management in the context of customer satisfaction. In both areas, there has thus far been a lack of theorising about the subject‐matter which might legitimately be encompassed within subject boundaries. By focusing on the single area of customer satisfaction an attempt is made to show how this process might proceed, albeit in a narrowly focused manner. The paper examines “hard” and “soft” dimensions to facilities management in hotels by means of an investigative probe into the nature of customer complaints in hotels. No claims are made for the generalisability of findings, rather it is the intention to show how, in the application of facilities management concerns, it is possible to engage in conceptual development and empirical study.

The purpose of this paper is to investigate the effects of capacity decisions regarding the number of servers/chefs and tables on identifying a change in the number of wait-related anxious customers, customer losses and customers served to meet the waiting time standards of an actual upscale restaurant.

The authors applied a simulation model to present the consequences of restaurant capacity decisions based on waiting time standards. Arena Simulation Software, licensed by Rockwell Automation, was used for modeling and identifying distributions of the data set provided by the restaurant. An experiment was designed for an upscale restaurant with existing five servers/chefs and 50 tables by changing these resources to measure the changes in customers' wait-related anxiety and other service performance indicators.

The results showed that an additional server/chef on weekends decreases the daily average number of anxious customers by nearly 33% and increases the daily average number of customers served by nearly 3% and has a little positive effect of decreasing customer losses. Table insertion for high- and low-requested seating areas had an only positive effect on decreasing customer losses.

In this study, the service capacity is dependent on waiting time, and it is addressed to study the relationship with customers' wait-related anxiety, which is a subjective metric. This study developed a point of view for identifying anxious customers whose waiting times are much longer than their cooking and delivery duration expectations regarding their meal preferences in the cooking stage and waiting experiences in the service entry.

This qualitative research aimed to explore the relationship between adaptive dynamic capabilities and resident loyalty formation among African-ethnic restaurants (AERs) during COVID-19 in East Africa.

Anchored on the dynamic capabilities perspective, the study uses eight case studies to obtain data based on restaurant owner-managers' lived experiences.

The paper presents six factors: (1) sensory quality promise, (2) service personalization declaration, (3) openness of technology adoption, (4) healthy food and safety assurance, (5) authenticity pledge and (6) diversity provision as prerequisites for resident loyalty formation. The findings suggest adaptive capacity as an appropriate alternative for stimulating resident loyalty formation during difficult times.

The findings help managers in formulating strategies that facilitate residents' display of willingness to revisit and/or recommend others. The local restaurants can now keep modifying and adjusting their practices and processes so as to exhibit the ability to handle customer unique demands during difficult times.

Through this work, a model of adaptive capabilities as enablers of resident loyalty formation is proposed, hence contributing the existing body of knowledge.