| Literature DB >> 33855230 |
Emigdio Larios-Gómez1, Laura Fischer2, Mónica Peñalosa3, Mayra Ortega-Vivanco4.
Abstract
This article explores the critical factors of consumption in Mexico, Ecuador, and Colombia, due to confinement and social distancing. Besides, which are the factors that influence the purchase decision. In the proposed model, we tested from quantitative research with a sample of 2,065 online consumers. We analyzed the following statistics: CFA, structural equations, invariance of measurement instruments, and multi-group analysis with the Smart Pls 3 and EQS 6.3 software. The study reveals that time, space, and place in the consumption process is more visible in the purchasing behavior with social distancing, healthy distance, and the commercial restriction caused by the health contingency. In addition to being a health and humanitarian crisis, the pandemic has severe economic consequences worldwide as 1) the increase in unemployment rates, 2) collapsed health systems, 3) education models overwhelmed by technology, 4) supply chains interrupted by the closure of borders, 5) international and domestic tourism suspended due to a lack of sanitary protocols,6) social coexistence curtailed by significantly increased infections and 7) a decreasing demand by consumers for the closure of companies. Despite being Latin American countries, cultural differences were not the priority of consumption in the crisis period due to Covid-19. They significantly change purchasing behaviors, and all have adapted to online and home delivery purchases by the social factor, local consumption, and consumers' attitude. The article presents several considerations on the main factors of consumption in Covid-19 in collectivist countries (North American and South America) such as Mexico, Colombia, and Ecuador and finds no substantial differences with consumers. There are practical implications for companies to adopt online channels and to create sales strategies in the face of the endemic pandemic.Entities:
Keywords: Business decision analysis; Commercialization; Consumer attitude; Consumption factors; Purchase behavior intercultural study México Colombia Ecuador; Purchase intention in times of pandemic
Year: 2021 PMID: 33855230 PMCID: PMC8027689 DOI: 10.1016/j.heliyon.2021.e06468
Source DB: PubMed Journal: Heliyon ISSN: 2405-8440
Purchase and consumption behaviors due to Covid-19.
| Immediate Effects of Purchase and Consumption | Facts on Consumer Behavior |
|---|---|
| Hoarding | Hygienic panic purchases in European countries such as Italy, Spain, and Germany, are repeated in the rest of the world's countries, including the Americas' region. |
| Improvisation | Before the Covid-19 pandemic, society reduced recycling, reusing, and recovering waste discarded for convenience and practicality. In this crisis period, weddings, funeral services, and religious celebrations realize through teleconference platforms. Besides scientific and academic meetings, concerts, and school through these platforms (such as Cisco EndPoint, Zoom, Microsoft Team, o Google Meet), we are replacing this traditional location and presence focused events with video conferences asynchronous and synchronous remote interaction. |
| Accumulated demand | The limitations of attending concerts, sports, bars, and restaurants and purchasing luxury products such as cars, jewelry, electronic devices, and even real estate. In addition to going for a walk through the streets, parks, or on the beach. Consumers, at the first opportunity in freedom of purchase, to purchase goods and services wildly, which they did not need but which satisfy the need to buy by buying after the sanitary closure just as it happened in Italy, France, Spain, and Germany, crowded beaches and shops like Zara. |
| Embracing digital technology | Facebook, YouTube, and WhatsApp, each with more than a billion subscribers and users, are the new platforms for communication, education, work, entertainment, health care, religion, and social interaction. Besides, WeChat, LinkedIn, TikTok, Instagram, Twitter, and WhatsApp have increased. In addition to the arrival and permanent positioning of streaming platforms such as Disney, Netflix, Amazon Prime, ClaroVideo, HBO, and Disney channel. |
| Adjustments to the working day | The provision of work and family times by employers has led consumers to increase their purchases of products at home, electronic payment with debit and credit cards, the consumption of prepared healthy food or not. They are provoking a change in consumer behaviors in schedules, days, quantities, and availability of brands, products, or services. |
| School meetings with friends and family | Elementary schools and even the university have graduated their students through virtual ceremonies and droid robots that have replaced the student's presence to receive their studies' certificate, but not the emotion and experience of living it directly. |
| Discovery of talent | YouTube increased the registration of channels by entrepreneurs of all ages, who either by losing their job or spending time at home due to the pandemic, have entered the networks to teach, share, commercialize or exchange goods and services made by themselves. Do-it-yourself channels in cooking, repairs, art, languages, academic knowledge, tourism, wellness, and health have increased. |
Figure 1North American country (as Mexico) Vs. South American countries (as Colombia and Ecuador). Source: (Hofstede, 2020a, Hofstede, 2020b).
The 6 dimensions of Hofstede: Mexico Vs. Colombia/Mexico Vs. Ecuador.
| Dimension | Mexico | Colombia | Δ | Ecuador | Δ |
|---|---|---|---|---|---|
| Distance power | 81 | 67 | 14 | 78 | 3 |
| Individualism | 30 | 13 | 17 | 8 | 22 |
| Masculinity | 69 | 64 | 5 | 63 | 6 |
| Uncertain dislike | 82 | 80 | 2 | 67 | 15 |
| Long-term orientation | 24 | 13 | 7 | - | - |
| Indulgence | 97 | 83 | 14 | - | - |
| (Δ) Delta=<30. |
Figure 2Hypothetical Model. Source: Own elaboration.
Demographic information of the samples.
| Variable | ítems | Mexico | Colombia | Ecuador | |||
|---|---|---|---|---|---|---|---|
| Frequency | % | Frequency | % | Frequency | % | ||
| Gender | Women | 642 | 64% | 359 | 55% | 254 | 64% |
| Man | 365 | 36% | 299 | 46% | 146 | 37% | |
| Age | from 18 to 25 years | 403 | 40% | 236 | 36% | 102 | 26% |
| from 26 to 43 years | 199 | 20% | 225 | 34% | 95 | 24% | |
| from 44 to 55 years | 176 | 17% | 104 | 16% | 149 | 37% | |
| from 56 to 65 years | 229 | 23% | 93 | 14% | 54 | 14% | |
| Marital status | Married | 312 | 31% | 211 | 32% | 141 | 35% |
| Singles | 695 | 69% | 444 | 68% | 259 | 65% | |
| Education | Basic | 9 | 1% | 13 | 2% | 19 | 5% |
| Average Superior | 171 | 17% | 164 | 25% | 113 | 28% | |
| Superior | 827 | 82% | 481 | 73% | 268 | 67% | |
Adapted scales.
| Construct | Factors (variables) | Ítems | Scale |
|---|---|---|---|
| Cultural factors | CN0_Cultura Nacional (Country) | ||
| Generational cohorts | PS1_Gender | ||
| Positive decision theory ( | Psychological factors (Attitude) | FP1.1_Humor before the Covid-19 | |
| Psychological factors (Health) | FP2.1_Exercise and Health | ||
| Psychological factors (Prediction) | FP3.1_Optimism | ||
| Social factors (Communication with others) | FS1.1_Use of Social Networks | ||
| Social factors (Personal) | FS2.1_Streaming movies | ||
| Economic factors (Sustainability) | FE1.1_Local Production | ||
| Economic factors (Basic consumption) | FE2.1_Reduction of plastics | ||
| Purchase behaviors | CC2_Compras Online |
Internal consistency and convergent validity of the theoretical model.
| Variable | Indicator | Loads | Value t | Cronbach's Alpha | CRI | AVE |
|---|---|---|---|---|---|---|
| Psychological factors (Attitude) | FP1.1_Humor before the Covid-19 | 0.858∗∗∗ | 22464 | 0.726 | 0.777 | 0.635 |
| FP1.2_Family Communication | 0.764∗∗ | 22.546 | ||||
| Psychological factors (Health) | FP2.1_Exercise and Health | 0.718∗∗ | 12.045 | 0.705 | 0.725 | 0.579 |
| FP2.2_Food changes | 0.928∗∗∗ | 40.662 | ||||
| Psychological factors (Prediction) | FP3.1_Optimism | 0.769∗∗ | 6.132 | 0.743 | 0.718 | 0.565 |
| FP3.2_Buy Insurance | 0.757∗∗∗ | 13.684 | ||||
| Social factors (Communication with others) | FS1.1_Use of Social Networks | 0.774∗∗ | 42.719 | 0.789 | 0.855 | 0.541 |
| FS1.2_Network Professional | 0.772∗∗ | 41.046 | ||||
| FS1.3_Using WhatsApp | 0.745∗∗ | 41.516 | ||||
| FS1.4_VideoconferenciaRecreativa | 0.741∗∗ | 37.958 | ||||
| FS1.5_VideoconferenciaProfesional | 0.765∗∗ | 32.693 | ||||
| FS1.6_Listen Radio (removed) | 0.523 | |||||
| Social factors (Personal) | FS2.1_Streaming movies | 0.703∗∗ | 22.250 | 0.758 | 0.734 | 0.581 |
| FS2.2_Streaming music and games | 0.731∗∗ | 26.022 | ||||
| FS2,3_Interest Kitchen | 0.716∗∗ | 15.148 | ||||
| Factores Economic factors (Sustainability)económicos (Sustentabilidad) | FE1.1_Local Production | 0.832∗∗∗ | 27.606 | 0.711 | 0.734 | 0.586 |
| FE1.2_Home Consumption | 0.764∗∗ | 12.042 | ||||
| Economic factors (Basic consumption) | FE2.1_Reduction of plastics | 0.722∗∗ | 2.557 | 0.708 | 0.776 | 0.508 |
| FE2.2_Changes Changes | 0.976∗∗∗ | 179.627 | ||||
| FS2.3_Environment (removed) | 0.508 | |||||
| Purchase behaviors | CC2_Compras Online | 0.752∗∗ | 43.926 | 0.743 | 0.803 | 0.578 |
| CC3_Increase in purchases | 0.848∗∗∗ | 99.058 | ||||
| CC1_Home Delivery | 0.752∗∗ | 14.169 |
S-B X2 5095,456 at 2150df; (S-B X2/df) 2.36; p- 0.000; RMSEA 0.065; NFI 0.825; NNFI 0.828; CFI- 0.845 - Parameters restricted to this value in the identification process; Level of significance ∗∗∗ á p < 0.001; ∗∗ á p < 0.05 CRI- Composite Reliability Index; AVE- Average Variation Extracted.
Internal consistency and convergent validity of the model adjusted by subsamples.
| Variable | CRI | AVE | CRI | AVE | CRI | AVE | CRI | AVE | CRI | AVE |
|---|---|---|---|---|---|---|---|---|---|---|
| MAN | WOMEN | MEXICO | COLOMBIA | ECUADOR | ||||||
| FP1 | 0.800 | 0.667 | 0.761 | 0.615 | 0.764 | 0.619 | 0.794 | 0.661 | 0.761 | 0.615 |
| FP2 | 0.725 | 0.586 | 0.724 | 0.573 | 0.781 | 0.548 | 0.739 | 0.594 | 0.713 | 0.560 |
| FP3 | 0.716 | 0.558 | 0.711 | 0.566 | 0.721 | 0.518 | 0.753 | 0.605 | 0.727 | 0.577 |
| FS1 | 0.856 | 0.543 | 0.854 | 0.539 | 0.855 | 0.542 | 0.859 | 0.550 | 0.834 | 0.503 |
| FS2 | 0.749 | 0.504 | 0.723 | 0.466 | 0.716 | 0.560 | 0.762 | 0.526 | 0.723 | 0.566 |
| FE1 | 0.720 | 0.584 | 0.730 | 0.575 | 0.735 | 0.582 | 0.755 | 0.608 | 0.751 | 0.601 |
| FE2 | 0.784 | 0.511 | 0.573 | 0.506 | 0.753 | 0.505 | 0.632 | 0.524 | 0.773 | 0.500 |
| CC | 0.807 | 0.583 | 0.802 | 0.575 | 0.747 | 0.501 | 0.839 | 0.635 | 0.780 | 0.544 |
Invariance test.
| Group | X2 | df | X2/df | RMSEA | SRMR | NFI | CFI |
|---|---|---|---|---|---|---|---|
| Mexico (n = 1007) | 2345.009 | 1410.58 | 1.66 | 0.050 | 0.084 | 0.956 | 0.960 |
| Colombia (n = 658) | 1918.863 | 921.45 | 2.08 | 0.046 | 0.085 | 0.937 | 0.977 |
| Ecuador (n = 400) | 1090.747 | 784.00 | 1.39 | 0.047 | 0.087 | 0.983 | 0.983 |
| Equal Form | 5353.881 | 2150 | 2.49 | 0.046 | 0.087 | 0.975 | 0.983 |
| Equal load factor | 5835.730 | 2258 | 2.58 | 0.049 | 0.087 | 0.973 | 0.978 |
Mexico Vs. Colombia-Ecuador: Hypothesis 1.
| Hypothesis | R2 Differences | R2 permuted | P-value Permutation | Result |
|---|---|---|---|---|
| H1: Mexico Vs. Colombia-Ecuador | -0.121 | -0.006 | 0.009 | Accepted |
Mexico Vs. Colombia-Ecuador: Hypothesis 2,3 y 4.
| Hypothesis - Relationships | Path (β) | t-value >1.96 | P-value <.05 | Result |
|---|---|---|---|---|
| H2: FP-1 MEN - > CC-CONS (psychological factors Mental Attitude) | 0.036 | 1.398 | 0.163 | Rejected |
| H3: FE1-NAC - > CC-CONS (economic factors Consumption of local) | 0.059 | 2.526 | 0.012 | Accepted |
| H4: FS1-COM - > CC-CONS (social factors family and Friends) | 0.150 | 5.957 | 0.000 | Accepted |