Survey Data on Permanence Factors in Restaurant Businesses: Ciudad Obregón, Sonora, México
Description
This dataset contains survey data collected from owners and administrative managers of food and beverage establishments in Ciudad Obregón, Sonora, México. Data were gathered using a structured questionnaire adapted from Clark (2018) and validated for the regional gastronomic context. The instrument includes 30 Likert-scale items distributed across five variables: work motivation (MOTIVA_LAB), manager leadership (LIDERAZ_GER), technological innovation in processes (INNOVA_TEC), service quality (CALIDAD), and business permanence (PERMANENCIA), with six items per variable. The dataset includes a total of 231 valid responses from restaurants identified through Mexico's National Statistical Directory of Economic Units (DENUE-INEGI), selected from a high commercial concentration area in the city. Additionally, five composite variables are included as the last five columns of the dataset, computed as the mean score of their corresponding items: Work Motivation (items MOTIV_LAB1– MOTIV_LAB6), Manager Leadership (items LIDERA_GER1– LIDERA_GER6), Technological Innovation (items INNOV_TEC1–INNOV_TEC6), Service Quality (items CALI_SERV1–CALI_SERV6), and Business Permanence (items PERMA1–PERMA6).
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Steps to reproduce
A quantitative, correlational, and cross-sectional study was conducted. Restaurants were identified through Mexico's National Statistical Directory of Economic Units (DENUE) by the National Institute of Statistics and Geography (INEGI), filtering establishments classified under food and beverage preparation services located in a high-density commercial area of Ciudad Obregón, Sonora, México. This yielded a universe of 364 establishments. A self-administered questionnaire was applied to owners and/or administrative managers, obtaining 229 valid responses after data cleaning. The instrument, adapted from Clark (2018), consists of three sections: (1) respondent demographic data (tenure in the company and in the position); (2) company profile data (company age, number of employees, and sales variation over the past five years); and (3) thirty Likert-scale items across five variables: work motivation (WM), manager leadership (ML), technological innovation in processes (TI), service quality (SQ), and business permanence (BP), six items each. Five composite variables were then computed as the mean score of their corresponding items and are included as the last five columns of the dataset. Internal consistency was assessed using Cronbach's alpha in IBM SPSS v.26, yielding values above 0.70 for all variables: WM = .763, ML = .838, TI = .861, SQ = .704, BP = .743. A Structural Equation Model (SEM) was then estimated using IBM SPSS Amos with maximum likelihood estimation. Items with low factor loadings were removed (WM2, WM3, WM5, WM6; SQ1, SQ4, SQ5, SQ6; BP1, BP2, BP3, BP6), and theoretically justified covariances between measurement errors were incorporated. Model fit was evaluated using: χ²/df = 1.762, CFI = .963, TLI = .951, GFI = .918, RMSEA = .058, SRMR = .0556, all meeting recommended thresholds.