Quality assurance in supply chains during the COVID-19 pandemic: empirical evidence on organisational resilience of conformity assessment bodies

Abstract

Global supply chains rely on the compliance and safety of their products, processes, and facilities. These vital services (often referred to as ‘quality assurance’ or ‘conformity assessment’ services) are provided by Conformity Assessment Bodies (CABs). This empirical study explores the impact of the COVID-19 pandemic on CABs as well as their response to the resulting challenges. Data was gathered through an online survey among all accredited CABs in Germany, which resulted in 555 valid responses. Taking a resilience perspective, we reveal that CABs were hit hard by the disruptions caused by the pandemic, albeit to different degrees, in part due to their type of services, size, and sectors served. Furthermore, we find that contingency plans do not directly cushion order declines (as the main indicator of the economic impact of the pandemic) but rather indirectly through helping CABs respond more quickly, which in turn mitigates their order declines. However, our results show that contingency plans can also have adverse effects if they hinder flexible reaction to the crisis. The findings of our study help managers and policymakers learn from the COVID-19 pandemic and improve the resilience of the conformity assessment sector and quality assurance in the event of future crises.

Keywords:

• COVID-19
• supply chains
• conformity assessment
• quality assurance
• resilience
• contingency plan

Introduction

The infectious disease COVID-19, which was declared a pandemic by the World Health Organization in March 2020 (Johns Hopkins University & Medicine, 2021), triggered significant disruptions in global supply chains (Belhadi et al., 2021; Junior et al., 2021). Whilst some industries had to shut down production at the beginning of the pandemic (Bragatto et al., 2021), other industries (such as healthcare or food production) had to find ways to operate under restrictions (i.e. lockdown-related import restrictions and the shutdown of production and staff's on-site work to comply with social distancing rules (Nicola et al., 2020)).

Sustaining operations in global supply chains under these conditions has been challenging (Chowdhury et al., 2021): labour shortage, lockdowns, closure of borders, delays in shipments, and shortages of supply had ‘ripple effects’ throughout supply chains (Ivanov, 2020). Apart from the logistical and supply issues, actors along global supply chains also needed to ensure continued compliance and safety of their products, processes, and facilities (Castka & Searcy, 2021). These vital services (often referred to as ‘quality assurance’, ‘conformity assessment’ or ‘testing, inspection, certification – TIC services’) are provided by Conformity Assessment Bodies (CABs) – a network of organisations that are governed by international standards and that serve supply chains across the globe and across all industry sectors. Considering the high relevance of CABs to global supply chains and global economy (as well as their importance to the functioning of practically all sectors), this study addresses fundamental questions about the resilience of CABs and thus the continued availability of their services in times of crisis.

Supply chain resilience during the pandemic has been addressed in various studies, mostly covering different elements or phases of resilience (Duchek, 2020) centred around preparedness, response/adaptation, and recovery/adjustment (Chowdhury et al., 2021). Against the backdrop of the extraordinary nature of the current crisis, scholars integrated new perspectives to the traditional resilience concepts. Examples are ‘viability’, which focuses on the need of actors in the supply chain securing goods and services for society to survive (Ivanov, 2020; Ivanov & Dolgui, 2020), or ‘antifragility’ (based on earlier work of Taleb (2012)), which takes a more positive approach towards disorder by highlighting that organisations can also gain from the current crisis (Nikookar et al., 2021).

We build on these studies and add to the growing literature that covers the impact of the COVID-19 pandemic in the domain of quality assurance and conformity assessment. Only a few studies have analysed the provision of these vital services in the pandemic, focusing either on certification and remote activities (Castka et al., 2020a; Nowicki & Kafel, 2021) or on challenges encountered by laboratories using a single case study (Ahmed et al., 2020). Yet, no comprehensive empirical study has explored how CABs at large were affected by the COVID-19 pandemic, how they responded to the associated challenges, and how their organisational resilience helped them cope with the crisis.

The context of quality assurance and conformity assessment also provides an important insight into the resilience of organisations that have not experienced major crises in the past. The ‘crises’ in the past were mostly related to the credibility of the services that these organisations provide (Prajogo et al., 2021). For example, deception in product testing services (and their verification) has been central to scandals such as the Poly Implant Prothèse (PIP) scandal (Martindale & Menache, 2013; Rott, 2019), VW's Diesel gate, or food scandals such as the presence of horse DNA in beef products (Bartram, 2018).

The previous COVID-19 related supply chain studies are seldom grounded in theory and lack empirical focus (Chowdhury et al., 2021) – a limitation that we address in our paper. We provide empirical evidence on the resilience of CABs during the pandemic. The empirical data comprises 555 accredited CABs in Germany, where the survey was conducted in June 2020. We conceptualise resilience based on a model by Fraunhofer EMI (2020) and analyse CABs’ preparedness, response to the crisis, and their performance. We conduct multivariate ordinary least squares (OLS) regression analyses to estimate the effects of variables that are critical to the provision of CABs’ services and hence their resilience; namely response time (as a resilience indicator) and order development (as an indicator of economic impact).

The remainder of this paper is structured as follows. First, we introduce our contextual and conceptual background. Afterwards, we present our methodology and the results of our data analysis. Following the discussion, we conclude with a summary of our contributions, limitations, and promising avenues for future research.

Contextual background

Quality assurance, or more precisely, conformity assessment, is a central element of the national quality infrastructure (Blind, 2015). Quality infrastructure is the “system comprising the organizations (public and private), together with the policies, relevant legal and regulatory framework, and practices needed to support and enhance the quality, safety and environmental soundness of goods, services and processes” (UNIDO, 2017). The services in this system are provided by Conformity Assessment Bodies (CABs), such as testing, calibration, and certification, and serve to demonstrate whether and to what extent goods and services conform to the requirements set, for example, by standards and regulations (ISO/IEC, 2020). In this way, trust and transparency in markets and supply chains, as well as reduced information asymmetries in economic activity, are ensured (Blind et al., 2018; King et al., 2005; Potoski & Prakash, 2009; Terlaak & King, 2006). The quality infrastructure plays an important role in the functioning of markets, with CABs providing a link between regulators, industry, and markets (UNIDO, 2020a). Previous studies indicate a substantial positive economic impact related to accredited conformity assessment services, in particular promoting innovation (Gonçalves & Peuckert, 2011), facilitating trade (Blind et al., 2018), and fostering economic growth (Frenz & Lambert, 2014; Teichler et al., 2013). Besides these economic benefits, the services also contribute to the protection of health, safety, and the environment (ISO & UNIDO, 2010). For example, third-party certifications have been found to increase product safety (IFIA & CEOC, 2018), testing against tolerable toxicity levels to enhance health (Källgren et al., 2003), or proficiency testing to monitoring emissions (environment) (Squirrell, 2008).

The COVID-19 pandemic has strongly affected CABs worldwide (Summers & Charrington, 2020). On the one hand, CABs experienced a decreasing demand for their services from heavily affected industries such as manufacturing, tourism, aviation, and hospitality – which ultimately has put the CABs’ economic viability at risk (UNIDO, 2020b). On the other hand, CABs had to rapidly address the increasing demand for certification of protective equipment, new products, and the increased demand to inspect and approve facilities that transform their production, e.g. from the manufacturing of cosmetics to the production of hand sanitisers (Castka & Searcy, 2021). CABs also experienced increased demand from the pharmaceutical sector (Ayati et al., 2020), with medical laboratories, for example, being crucial in the development of vaccines and treatments helping to overcome the COVID-19 pandemic (Ibeh et al., 2020). Yet, pandemic-related restrictions and challenges, such as staff shortages, travel bans, or shortages of materials supply (e.g. personal protective equipment and consumables for laboratory testing), have often impaired CABs’ ability to offer such services (Giacobbea & Bempooradb, 2020; Pecchia et al., 2020).

Theoretical background – organisational resilience

Organisational resilience refers to the ability to adapt and respond to challenges and anticipate threats (Barasa et al., 2018; Bryce et al., 2020). This ability to cope with crises such as the COVID-19 pandemic has increasingly attracted the interest of researchers (Belhadi et al., 2021; Bragatto et al., 2021; Ivanov, 2020; Rai et al., 2021). For instance, Bragatto et al. (2021) propose a theoretical framework to measure organisations’ efforts to increase their resilience during the COVID-19 crisis around the four phases of “anticipate, monitor, react and learn” (Hollnagel et al., 2006) and construct a ‘resilience indicator’. Belhadi et al. (2021) investigate supply chain resilience using the results of a survey among managers in the automotive and aviation industry. They focus on the time to recover and the financial impact of the COVID-19 pandemic for the short-term and long-term strategies and reveal the importance of localised supply sources and the use of digital technologies among others (Belhadi et al., 2021). Rai et al. (2021) conducted a multiple-sector study and investigated the impact of the three components of resilience – crisis anticipation, organisational robustness, and recoverability – on social and economic sustainability during the COVID-19 pandemic. The authors find a positive relationship between them. Nikookar et al. (2021), referring to Taleb's (2012) concept of ‘antifragility’, argue that companies can actually gain from disorder by embracing the opportunities that emerge through crises. The COVID-19 pandemic is a striking example of disorder. In this context, companies and supply chains are not necessarily attempting to return to the old normal but “preparing for a future of continual’ change” (Nikookar et al., 2021).

Ivanov (2020) conceptually analyses the role of resilience through the lens of ‘viable supply chains’ that are “able to absorb negative disturbances, recover and survive during short-term disruptions and long-term, global shocks” such as the COVID-19 pandemic. Ivanov and Dolgui (2020) apply the concept of viability to intertwined supply networks (ISN), which are defined as “an entirety of interconnected supply chains (SC) which in their integrity secure the provision of society and markets with goods and services”. Given their structural dynamics and particular importance in providing services to society, which are needed for its long-term survival, the authors propose to apply the concept of viability which focuses on the ISN's ability to sustain itself and recover from disruptions over a long-term horizon. According to Ivanov and Dolgui (2020), quality management control is a major area for consideration in accordant modelling.

In the context of quality infrastructure, based on a survey among German organisations, Blind and Heß (2021) investigate the resilience in standardisation during the COVID-19 pandemic. They find that, particularly due to remote activities, standardisation activities could be sustained by organisations, with the advantage of decreasing costs (mainly related to travel costs), but with the disadvantage of a lack of informal exchanges needed, for instance, for reaching a consensus.

We apply the concept of organisational resilience as a theoretical framework to our analysis of the resilience of CABs. Figure 1 depicts how the resilience of CABs can be determined based on performance evaluation during the different phases of the crisis, with organisations needing to take measures and methods "required to make optimal decisions before, during and after a crisis" (Fraunhofer EMI, 2020). The resilience model depicts the aim of organisations to minimise the drop in performance when crises occur by being prepared and taking precautionary measures (prepare and prevent) in the first place. For instance, contingency plans developed in the pre-crisis period serve to provide guidance in the event of a crisis. This so-called static resilience is thus "founded on preparedness and preventive measures to minimize threats probability and to reduce any impact that may occur" (Annarelli & Nonino, 2016). Then, at the beginning of the crisis, protection becomes important to safeguard the functioning of critical infrastructures and to have systems in place to cope with the situation. During a crisis, the response time of organisations is a key determinant of resilience. Annarelli and Nonino (2016) refer to this as dynamic resilience that is "founded on the ability of managing disruptions and unexpected events to shorten unfavourable aftermaths and maximize the organization's speed of recovery to the original or to a new, more desirable state". After the crisis, organisations, in the best-case scenarios, can also benefit from the crisis if they are able to learn from it for future crises (Fraunhofer EMI, 2020).

Figure 1. Resilience model of Fraunhofer EMI (2020).

Methodology and sample

We apply the resilience model of Fraunhofer EMI (2020) to investigate how the COVID-19 pandemic has affected Conformity Assessment Bodies (testing, calibration, medical laboratories, certification bodies, and other CABs) in Germany to explore their resilience in the pre-crisis, within-crisis and, post-crisis periods. First, we present the sample and compare the key characteristics of the CABs surveyed. Second, we present the descriptive statistics highlighting significant differences between various types of CABs (such as activity offered) by using t-tests, with the corresponding p-values presented in the accordant figures and tables. Third, we conduct an Ordinary Least Squares (OLS) analysis to investigate the impact of resilience-related factors as well as external factors (such as sectors served) on CABs’ economic performance, which we operationalise with their order development as our dependent variable of primary interest. Although our sample encompasses ordinal variables, we treat them as metric ones to run our statistical analysis (see Kampen & Swyngedouw, 2000). For our statistical analysis, we use the statistics software QResearch (Displayr, 2020) and Stata version 16 (StataCorp, 2019).

Out of the 3,204 CABs in the database of the German national accreditation body DAkkS that we invited to participate in our online survey in June 2020, 555 filled out our questionnaire, equalling a response rate of 17%. Table 1 gives an overview of our sample composition. In our analysis, we differentiate between testing and calibration laboratories (ISO/IEC 17025), medical laboratories (ISO 15189), and certification bodies for products, management systems, and persons (ISO/IEC 17065; ISO/IEC 17021–1; and ISO/IEC 17024). The other CA activities (such as inspection (ISO/IEC 17020), validation & verification (ISO/IEC 17029), proficiency testing (ISO/IEC 17043), and production of reference material (ISO 17034) are grouped as ‘other’. It is noteworthy that one single CAB can offer more than one CA activity, e.g. testing as well as certification services. 77% of the sampled CABs offer only one CA activity, 15% offer two activities, and the remaining 8% offer up to 7 activities. Thus, the aggregate number of CA activities is 749 for the 555 CABs surveyed.

Table 1. Sample description.

	All N=555	Testing laboratories N=352	Calibration laboratories N=125	Medical laboratories N=36	Certification bodies N=160	Other N=76
Main sectors served*
Manufacturing	59%	55%	91%	11%	62%	63%
Primary sector	15%	17%	8%	11%	14%	10%
Environmental sector	19%	22%	11%	17%	17%	4%
Construction	11%	14%	5%	3%	27%	17%
Health	20%	18%	12%	92%	12%	19%
Other	18%	18%	14%	8%	30%	27%
Company size
<10 employees	37%	30%	48%	11%	31%	16%
10–49 employees	38%	40%	31%	22%	37%	29%
50–250 employees	16%	20%	7%	44%	18%	29%
Over 250 employees	9%	11%	12%	19%	13%	26%
Internationally active
Yes	66%	63%	82%	64%	84%	77%
No	35%	37%	18%	36%	16%	23%
Operational focus
External CAB (CA is focus of organisation)	39%	38%	28%	17%	58%	44%
External CAB (CA is one business field among others)	36%	33%	56%	25%	36%	43%
Internal CAB	15%	18%	13%	19%	0%	6%
Other	10%	10%	2%	39%	7%	7%

* Note: CABs could choose up to 3 micro-sectors served; hence, the total sum adds up to more than 100%. For sector composition, see Koch et al. (2020).

Based on the number of accreditations, testing is by far the prevalent conformity assessment activity in general, with over 50% of CABs in Germany and throughout Europe engaging in it, followed by certification bodies (14%) and calibration and medical laboratories (∼ 12% each). With regard to the generalisability of our results, we find that our sample reflects well the distribution of the total population in the DAkkS database, with only minor deviations regarding the share of individual CA activities (Koch et al., 2020) which, we argue, allows a first characterisation of accredited CABs in Germany.

The results of our survey can be differentiated according to the sectors the CABs are serving, their size, and whether they are internationally active. Further, we distinguish if their operational focus is CA services to external customers (in the following referred to as ‘external CABs’) or whether they are part of a company that they serve as an accredited internal CAB (in the following referred to as ‘internal CABs’). Such internal CABs are mainly found among medical but also other laboratories and – unsurprisingly – not among certification bodies, which by definition perform third-party assessments (ISO/IEC 17000). Overall, 15% of respondents considered themselves as internal CABs. The vast majority (75%) of respondents were small enterprises with less than 50 employees. However, it is noteworthy that CABs oftentimes rely on contractors, e.g. to conduct audits, which are not counted as CABs’ permanent employees. The main sector served by the CABs in our sample is manufacturing, especially for calibration laboratories, apart from medical laboratories, which mainly provide services to the health sector.

Results – descriptive analysis

In this section, we present the results of the survey following the resilience model presented in Figure 1. Our analysis firstly focuses on the evaluation of CABs’ performance. Second, we analyse CABs’ resilience following the pre-crisis, within-crisis, and post-crisis stages of the resilience model.

Performance of CABs during the crisis

Resilience contributes to minimising the drop in performance when crises occur. As measures of this performance, we assessed the economic situation of the Conformity Assessment Bodies (CABs) during the pandemic as well as their ability to operate. Respondents were asked to evaluate the impact of the COVID-19 pandemic on their order demand (compared to pre-crisis levels) on a scale from −2 (strong decrease) to +2 (strong increase). The results show that the pandemic has had economic consequences for all conformity assessment (CA) activities (Figure 2): 63% of them faced order declines, whilst only 5% experienced increases in demand for their services. On average, calibration was the most severely affected activity (mean = −0.93). In contrast, medical laboratories reported the lowest average decline in orders: One in four even benefited from order increases.

Figure 2. Order demand development with mean values (right). ***p<0.01, **p<0.05, *p<0.1 Question: What influence does the COVID-19 pandemic have on the order development of your organisation with regard to your conformity assessment services (compared with the pre-COVID-19 period)?

The degree to which the CABs are affected also depends on whether they are an internal or external CAB: 46% of internal testing laboratories have experienced a decline in orders, while this is the case for 67% of testing laboratories serving third parties. This tendency is even more pronounced for calibration laboratories (with 33% for internal vs. 77% for external CABs) and medical laboratories (with 33% for internal vs. 76% for external CABs) facing variating order declines.

Performance was also affected by the ability of CABs to continue operations under the COVID-19-related restrictions. Here, we find that almost one in four CABs was able to pursue their operations normally in the pandemic. This condition was most common among medical laboratories (42%), whilst certification bodies were most likely to be restricted in their operations. Nevertheless, complete shutdowns of business activities remained the exception across all types of CABs.

Despite the predominantly negative impact of the COVID-19 pandemic, only 1% of the surveyed CABs fear an immediate threat to their economic viability, while two-thirds see no immediate threat. However, one in three CABs foresees a threat if no fundamental change in the economic situation occurs within the next six months (as of the time the survey was taken). This is particularly the case for external CABs. Almost 32% of them perceive such a threat, while only one in five internal CABs shares this fear.

The existential struggles CABs are facing have been partly alleviated by governmental support measures. The German government, similar to other governments worldwide, responded to the pandemic by introducing wage subsidies, but also loans, subsidies, and tax credits (Federal Ministry of Finance, 2020). In our sample, 36% of CABs reported having applied for government support (Table 2). CABs have taken advantage of such governmental assistance to a varying degree. Medical laboratories were significantly less likely to apply for support measures compared to other CA types, which is not surprising given the less severe order decline they faced (see Figure 2).

Table 2. Application for government support.

	All N=538	Testing laboratoriesN=340	Calibration laboratories N=124	Medical laboratoriesN=33	Certification bodies N=118
Yes	36%	33%	48%	27%	36%
No	56%	60%	40%	49%	58%
I don‘t know	8%	7%	12%	24%	6%

Question: Did your organisation apply for government support during the COVID-19 pandemic? (related to CA).

Most of the CABs applied for Germany's short-time work scheme, which is ‘a social insurance program whereby employers reduce their employees’ working hours instead of laying them off’ (IMF, 2020). 25% of all surveyed CABs applied for this short-time work (especially smaller CABs with less than 50 employees), while 4% applied for emergency aid (especially micro-enterprises with less than ten employees). Another 6% of CABs reported having applied for both measures. However, the extent to which CABs applied for government support was independent of the operational focus of CABs.

Pre-crisis: prepare & prevent

Resilience encompasses measures taken before, during, and after a crisis (Figure 1). Resilience depends on manifold factors, such as material and human resources, preparedness, or processes (Barasa et al., 2018). The survey aimed to assess how resilient the CA sector is, i.e. how well prepared and able CABs were to adapt and respond to extraordinary challenges such as the COVID-19 emergency, focusing on the availability of a contingency plan and needed IT resources.

Contingency plans contain appropriate planned procedures for dealing with extraordinary events or circumstances and can thus help to manage crises better (Fraunhofer EMI, 2020). Half of the CABs did not have a contingency plan before the pandemic began; only about 38% did so (Table 3). Overall, medical laboratories stand out as the frontrunners, with 75% of them having had a plan. Organisational size matters: medium-sized and large organisations were more likely to have such a plan in place than small CABs (one-third vs. half of these CABs).

Table 3. Availability of a contingency plan.

	All N=552	Testing laboratoriesN=351	Calibration laboratoriesN=124	Medical laboratoriesN=33	Certification bodiesN=118
Yes	38%	37%	40%	75%	39%
No	51%	52%	46%	14%	50%
I don‘t know	11%	11%	14%	11%	11%

Question: Before the COVID-19 pandemic, did your conformity assessment body have a planned procedure for dealing with exceptional events or circumstances?

Whether firms are able to successfully cope with crises also depends on the availability of their resources (Fraunhofer EMI, 2020). For example, Marcucci et al. (2021) highlight the importance of IT and find a positive relationship between IT-related technologies (such as cloud computing) and organisational resilience and company performance.

In our survey, more than 80% of CABs reported that the necessary IT resources were available (Figure 3), with calibration laboratories standing out positively (91%). Internationally active CABs were less likely to report a lack of IT resources than CABs serving only domestic customers (16% vs. 24%). Similarly, CABs serving the environmental sector were significantly less prepared in terms of their IT infrastructure, with only 52% of respondents operating in the sector reporting that the available resources were sufficient. In contrast, CABs serving the manufacturing industries were comparatively well-prepared (85%).

Figure 3. Availability of IT Resources *** p<0.01, ** p<0.05, * p<0.1 Question: At the beginning of the COVID-19 pandemic, were the necessary IT resources present and available within your conformity assessment body to deal with the challenges associated with the Corona pandemic?

Within-crisis: respond & recover

An important resilience-related factor on the recoverability is how fast organizations are able to respond to changes (Rai et al., 2021). We measure this as the pace by which CABs were able to respond to challenges resulting from the COVID-19 pandemic (response time).

The vast majority of respondents (86%) reported having responded rather quickly to the challenges related to the pandemic, 48% even very quickly, with only minor differences across the various CA activities (Figure 4). Only 2% did not react or responded very slowly.

Figure 4. Response time with mean values (right) *** p<0.01, ** p<0.05, * p<0.1 Question: How quickly did your organisation respond to the challenges resulting from the COVID-19 pandemic?

Figure 5. Capability to learn from crises with mean values (right) ***p<0.01, **p<0.05, *p<0.1. Question: How do you assess the capability of your organisation to learn from the experience of the COVID-19 pandemic and to learn from the experience of the Corona pandemic and take any necessary adaptation measures?

Internal CABs reported a faster response time, with 62% claiming they reacted very quickly. The same is true for medium-sized companies (58% ‘very quickly’ compared to 42% for small CABs with less than ten employees).

Post-crisis: learn

Respondents were largely positive about their ability to learn from the pandemic and make necessary adjustments. 64% rated their learning ability as very high or rather high. For internal CABs, the figure is as high as 74%. Only 7% of respondents rated their own organisation's ability to learn as rather low or very low. Differences among CA activities are evident: Medical laboratories were the most confident in assessing their learning ability. In contrast, one-third of testing and calibration laboratories assessed their capability as either very low or low, resulting in lower mean values compared to other CABs (Figure 5).

Confidence in one's learning capability was further affected by structural aspects. Confidence tended to increase with greater organisational size. Companies with less than ten employees showed a significantly lower constructed mean value than CABs with more than 1000 employees (3.7 vs. 4.2). Internal CABs were also significantly more positive in their assessment of organisational learning (average mean value of 4.1).

Results - multivariate regression analysis

To estimate the effects of various variables, first on response time as a resilience indicator and second on order development as the main indicator of the economic impact of the pandemic on CABs, we conducted multivariate OLS regression analyses with the variables depicted descriptively in Table 4.

Table 4. Description of variables.

	N	mean	SD	p50	min	max	Description
Dependent variables
Response time (from 0 to 4):
All	523	3.4	0.72	4	0	4	Response time for all
Testing	331	3.38	0.75	3	0	4	Response time for testing labs
Calibration	115	3.37	0.68	3	1	4	Response time for calibration labs
Certification	116	3.44	0.59	3	2	4	Response time for certification bodies
Order development (from -2 to +2):
All	551	-0.83	0.86	-1	-2	2	Order development for all
Testing	350	-0.83	0.87	-1	-2	2	Order development for testing labs
Calibration	119	-0.93	0.73	-1	-2	1	Order development for calibration labs
Certification	121	-0.75	0.9	-1	-2	2	Order development for certification bodies
Independent variables
Resilience-related
Contingency plan	495	0.43	0.5	0	0	1	Availability of contingency plan*
IT resources	526	0.81	0.39	1	0	1	Availability of necessary IT resources*
Control variables
Employees	551	102.7	230.4	30	5	1100	Absolute number of employees at CAB**
International	495	0.43	0.5	0	0	1	CABs with international activity*
Manufacturing	555	0.81	0.39	1	0	1	Manufacturing industry served*
Primary sector	555	0.15	0.36	0	0	1	Primary sector served*
Environmental	555	0.18	0.38	0	0	1	Environmental sector served*
Construction	555	0.11	0.32	0	0	1	Construction sector served*
Health	555	0.20	0.4	0	0	1	Health sector served*
Other sector	555	0.21	0.41	0	0	1	Other sectors served*
Internal CAB	555	555	0.15	0.5	1	0	Internal CAB*

* Dummy variable: yes=1/ no=0

** calculated as mean value for the six groups 1–9, 10–49, 50–249, 250–499, 500–999, 1000 and more

Table 5 presents the results of the eight models. Models 1–4 estimate the influence of a contingency plan on the response time as well as other potentially influencing factors. Models 5–8 estimate the effect of response time and the other variables on order development. For each dependent variable, we consider the sample of all Conformity Assessment Bodies (CABs) surveyed (excluding CABs with missing answers), and in addition, for testing laboratories (excluding medical laboratories), calibration laboratories, and certification bodies separately to conduct sub-sample analyses.

Table 5. Regression results.

	(1)	(2)	(3)	(4)	(5)	(6)	(7)	(8)
	Response time	Response time	Response time	Response time	Orderdevelopment	Orderdevelopment	Orderdevelopment	Orderdevelopment
	All	Testing	Calibration	Certification	All	Testing	Calibration	Certification
Resp. Time					0.100*	0.0731	-0.0445	0.212
					(0.0575)	(0.0699)	(0.125)	(0.168)
Cont. Plan	0.225***	0.215**	0.0464	0.168	-0.164**	-0.215**	0.0101	-0.312*-
	(0.0666)	(0.0908)	(0.130)	(0.116)	(0.0823)	(0.107)	(0.153)	(0.186)
IT resources	0.254***	0.200*	-0.120	0.604***	0.150	0.196	-0.150	0.208
	(0.0864)	(0.110)	(0.245)	(0.146)	(0.106)	(0.130)	(0.283)	(0.251)
# Employees	7.90e-05	3.38e-05	0.000433*	-1.18e-05	5.67e-05	0.000476*	0.000436	5.44e-06
	(0.000151)	(0.000204)	(0.000259)	(0.000189)	(0.000188)	(0.000247)	(0.000330)	(0.000298)
International	0.0493	-0.102	0.397***	0.108	-0.111	-0.0569	0.151	-0.169
	(0.0677)	(0.0936)	(0.133)	(0.114)	(0.0826)	(0.110)	(0.164)	(0.180)
Manufacturing	-0.0207	0.0519	0.261	-0.0258	-0.401***	-0.493***	-0.390	-0.275
	(0.0800)	(0.108)	(0.253)	(0.127)	(0.0977)	(0.127)	(0.318)	(0.200)
Primary sector	0.0154	-0.0325	0.300	0.229	0.0233	0.0405	0.379	-0.0426
	(0.0954)	(0.127)	(0.228)	(0.164)	(0.116)	(0.149)	(0.280)	(0.261)
Environmental	-0.0499	-0.0104	-0.0129	-0.220	0.00190	-0.145	-0.193	0.563**
	(0.0868)	(0.112)	(0.229)	(0.164)	(0.106)	(0.131)	(0.266)	(0.262)
Construction	-0.0422	-0.100	0.303	-0.0729	0.242*	0.0411	0.251	0.530**
	(0.108)	(0.136)	(0.366)	(0.138)	(0.132)	(0.160)	(0.426)	(0.218)
Health	-0.0454	-0.125	-0.303	0.0401	-0.00902	-0.290**	0.0464	0.841***
	(0.0890)	(0.119)	(0.200)	(0.196)	(0.109)	(0.140)	(0.252)	(0.309)
Other sector	0.181**	0.190*	0.410**	0.0821	0.0831	0.0510	0.0214	0.0643
	(0.0817)	(0.110)	(0.188)	(0.125)	(0.100)	(0.129)	(0.232)	(0.197)
Internal CAB	0.244***	0.162	0.503***	0.599	0.477***	0.361***	0.743***	-0.147
	(0.0898)	(0.115)	(0.184)	(0.396)	(0.111)	(0.136)	(0.226)	(0.633)
Constant	3.039***	3.151***	2.853***	2.812***	-1.061***	-0.922***	-0.543	-1.528***
	(0.112)	(0.145)	(0.361)	(0.204)	(0.222)	(0.279)	(0.568)	(0.572)
Observations	460	292	97	100	456	290	93	100
R-squared	0.088	0.076	0.248	0.312	0.128	0.134	0.234	0.240

*** p < 0.01, ** p < 0.05, * p < 0.1.

We find a significant and positive effect of contingency plans on response time for the full sample (Model 1), which is also the case for the largest sub-sample of testing laboratories (Model 2) but not for other CAB types (Models 3-8). The availability of IT resources also has a significant and positive effect on response time for the full sample (Model 1). Besides testing laboratories (Model 2), this effect is particularly strong for certification bodies (Model 4), indicated by its high coefficient. Calibration laboratories neither benefit significantly from the availability of a contingency plan nor IT resources to respond more quickly to the challenges of the COVID-19 pandemic (Model 3). For them, however, the company size and international orientation play a role: Larger and more internationally active calibration laboratories were able to respond comparably faster. Finally, internal CABs have a quicker response in the full sample and calibration laboratories specifically (Models 1 and 3).

But did a quick response time actually mitigate a potentially sharp decline in orders? The coefficients in models 5–8 can help answer this question. For the full sample, a faster response time was, on average, associated with a positive and significant impact on order development at the 10% significance level. A counterintuitive finding, however, is that a contingency plan has a negative impact on order development for the full sample, especially for testing laboratories and certification bodies.

The results show that testing laboratories, in particular, suffered less from order declines if they were larger in size (referring to the number of their employees). Considering the sectors, the total group of CABs, as well as particularly testing and calibration laboratories serving the manufacturing sector, were the most heavily affected in our regression analysis. Surprisingly, we find a negative and significant effect on order development for testing laboratories when serving the medical sector, while this sector effect is positive and significant for certification bodies. We also find a positive and significant effect for certification bodies serving the construction and environmental sector. Internal CABs generally suffered less from order declines, with the impact being highest for calibration laboratories.

Discussion

We have applied a resilience framework (Fraunhofer EMI, 2020) to theoretically underpin the impact of the COVID-19 pandemic on accredited Conformity Assessment Bodies (CABs) in Germany, their response to the crisis, and their performance. For our following discussion, we furthermore extend the ‘traditional’ resilience view (Figure 1) with the above presented more recent concepts of viability and antifragility.

Our study provides empirical evidence of how CABs were affected by the pandemic economically (specifically regarding the demand for their services), their emergency preparedness (i.e. availability of IT resources), their response (e.g. application for governmental support), response time, and their ability to learn from the crisis. Our findings are broadly in line with previous resilience literature, highlighting the importance of planning and preparedness, especially in increasingly complex environments and transboundary crises (Bryce et al., 2020). In the context of the COVID-19 pandemic, studies have underlined the importance of digital capabilities and resources (Guo et al., 2020; Juergensen et al., 2020) to ensure continuity of processes and services and safeguard interactions among employees and with external stakeholders (Papadopoulos et al., 2020)

As the analysis demonstrated, differences were observed according to the types of conformity assessment (CA) activities, organisational characteristics, and sectors served. The COVID-19 pandemic triggered considerable disruptions in most industry sectors due to supply shortages and imposed restrictions. These disruptions were eventually cascaded down to CABs. We argue that on a broader scale – given its importance within the whole Quality Infrastructure system – the CAB sector is an important part of intertwined supply networks (ISNs). Building on Ivanov and Dolgui's (2020) argumentation, this highlights the need to safeguard the survivability of CABs to ensure viability of the respective ISNs.

In Germany, on an aggregate level, turnover for businesses was 5.3% lower in the second quarter of 2020 compared to the same period in 2019 (Statistisches Bundesamt, 2021). For the sector of technical testing and analysis (NACE Rev. 2 Code 71.20), which comprises the majority of CA activities, the reduction amounted to −1.4% (Statistisches Bundesamt, 2021). Thus, the economic situation of CABs mirrored the development of the German economy as a whole during the pandemic. At the sectoral level, gross value added in the manufacturing sector fell by about 20% in Q2-2020 compared with Q2-2019 after being hit hard by shutdowns of production facilities and disruptions in global value chains at the beginning of the pandemic (Lerch et al., 2020; Statistisches Bundesamt, 2021). Our regression analysis showed that serving this sector resulted in a significantly more negative impact on the order demand of CABs. This proved particularly severe for calibration laboratories, 91% of which in our sample actually serve this industry. As our data show, calibration was the CA activity facing the largest order decline of all CABs.

The findings from the manufacturing sector are not surprising and indicate a close correspondence and interdependence (with a subsequent cascading impact) of the sector on CABs – given CABs’ essential role in providing the manufacturing sector a ‘license to operate’. Interestingly, in the case of the health sector, testing laboratories experienced a stronger decline in orders than other CAB types, whereas certification bodies benefited from serving this sector. The ability of certification bodies to offer digital services such as remote audits (Castka et al., 2020a) may have contributed to the increasing demand for certification bodies serving the medical sector. Having sufficient IT resources in place also enabled certification bodies to respond more quickly to the challenges of the COVID-19 pandemic (Table 5).

Facing the negative impacts on their economic situation and thus a drop in performance, our data show that 36% of surveyed CABs sought governmental assistance (Table 2). Comparing the proportion of CABs applying for support measures with the overall share of businesses explored in other studies reveals that the CA sector in Germany has a comparably lower propensity to seek financial aid. In a sector-wide survey of German companies, 70% of respondents claimed to have applied for governmental assistance in June 2020 (DIHK, 2020). The large discrepancy between CABs and companies from other sectors of the economy may be due to the fact that CABs in our survey were less likely to have suffered from a halt of business activity. In the rest of the economy, 21% of businesses faced the (almost) complete cessation of their operations (DIHK, 2020), compared to 17% of CABs in our survey. Since government aid, especially in the form of wage subsidies, was allocated primarily to businesses that were severely constrained in their operations, comparatively less constrained CABs may not have met the eligibility requirements. However, considering the continuous adaption of government support programmes and their extension to further areas of the economy, the share of CABs receiving aid might have converged with that of the overall economy over time. This consideration would have to be evaluated in a further survey, thus remaining tentative at this point.

To manage the crisis and prevent a drop in performance, resilience plays a crucial role. Here, the different stages of crisis and multiple facets need consideration, most importantly, the pre-crisis preparatory stage (i.e. development of contingency plans) and within-crisis response (i.e. immediate protection in response to the crisis to ensure continuity of operations, handling of the crisis and recovering). As our data show, the order development is influenced by response time. In turn, response time is positively affected by the availability of a contingency plan and IT resources. Therefore, our results show that accordant IT resources play a crucial role, but also preparation through contingency planning. We find evidence supporting findings from previous literature on ICT-related resilience (Bertschek et al., 2019). As other studies have outlined the meaning of proper contingency planning (Barasa et al., 2018), our data also found that it helps CABs to cope with the crisis.

These results give rise to the assumption that a contingency plan has a positive impact on order development as well since business continuity plans, for example, help to react in the event of emergencies (Bragatto et al., 2021). However, the results, in fact, yielded a negative relationship, which is particularly strong and significant for certification bodies (one type of CABs). Although counter-intuitively, there is no direct positive relationship, our data reveal a rather indirect positive relationship: We find the contingency plans improve the response time of the CABs, which in turn positively impacts order development. As a possible explanation for the effects of contingency plans, previous research has also highlighted situations in which a contingency plan may actually prevent organisations from responding quickly. In this sense, Smith (1990) discusses the limitations of contingency planning since it might distract organisations from making effective decisions and instead highlights the relevance of organisational culture. Similarly, Grewal and Tansuhaj (2001) emphasise flexibility and market orientation in crisis management. They point out that ‘proactive offensive action’ is oftentimes not appropriate, but rather ‘reactive strategic flexibility capability’, while an overly specific contingency plan might reduce the ability to respond flexibly (Grewal & Tansuhaj, 2001). Therefore, it seems that the static resilience founded on preparedness and preventive measures (Annarelli & Nonino, 2016) by itself is not sufficient to deal with the crisis.

Rather, during crises, dynamic resilience (founded on abilities to manage the crisis and learn from the crisis) is more important (Castka et al., 2018). Similarly, drawing from interviews with managers in the business-to-business field, Cortez and Johnston (2020) stress the need for strategic flexibility and conclude that the current COVID-19 crisis ‘presents a situation where the benefits of adaptation overcome the gains from standardization’ (Cortez & Johnston, 2020).

Referring to the concept of antifragility, Taleb (2012) uses the metaphor of the ‘soccer mom’, who aims to reduce all possible risks for her children but actually hinders their development by eliminating learning for a trial-and-error and thus reducing their capability to handle ambiguity in their future lives. Using this analogy of a ‘soccer mom’ within the concept of antifragility (Nikookar et al., 2021; Taleb, 2012), the existence of a contingency plan might thus have obstructed the successful crisis management of CABs.

However, our survey data do neither consider additional contextual aspects on the nature and extent of contingency plans nor on organisational cultures to draw more precise conclusions. Furthermore, the negative effect of contingency plans on order development in CABs might be due to the fact that the negative repercussions of the macroeconomic external demand shock exceeded the potential cushioning effect of contingency plans. In other words, the plans were not always able to halt the decline in demand.

Practical implications

The pandemic could be seen as a wake-up call for policymakers, the conformity assessment (CA) sector (and its key actors), as well as for global supply chains. Our paper has implications for all these stakeholders.

Policymakers and national governments are responsible for the quality infrastructure in their respective countries. Disrupted services, such as CA, can aggravate other economic disruptions and threaten the functioning of critical infrastructures and supplies (e.g. food and medical care). In that sense, policymakers should address the risk associated with underperforming actors in CA and project these risks into their strategies related to the national quality infrastructure. The key aspect is ensuring that Conformity Assessment Bodies (CABs) upgrade their IT systems and embed digitalisation and remote practices in their services. These measures will certainly involve adjustments and revisions of legal frameworks as well as governance rules for quality infrastructure. It is also important to ensure an appropriate status for CABs during crises. In many jurisdictions, at the onset of the pandemic, CABs have often not been considered ‘critical services’, despite their critical role in national economies and global supply chains. Categorising CABs officially as critical services would have provided them access to mitigating measures and the actuation of prioritisation and guidance measures (Galbusera et al., 2021). At the same time, such status might come with further obligations for contingency planning and crisis preparation, and our study can provide guidance for establishing such obligations for societal benefits. As our findings suggest, these measures combined – government support, contingency planning, and enforced digitalisation – will contribute to better responsiveness and thus fewer disruptions, making CABs more resilient.

Similar implications can be drawn for individual CABs. Investing in resilience-building will assist CABs in handling future crises and enhancing their competitive advantage in an increasingly digitalised economy. CABs’ level of digitalisation is low relative to other sectors (Raghavan et al., 2021), and the digitalisation efforts accelerated by the pandemic demonstrate the benefits associated with digitalisation. Therefore, a practical recommendation to CAB managers is to invest in adequate contingency planning and critically assess their capabilities and resources that would enable rapid response to challenges of potential future crises. For that, it is essential to draw conclusions from their performance in the pandemic, especially in the early stages, and implement improved measures in future critical situations. Likewise, other actors, such as accreditation bodies, standard-setting organisations, and auditors, need to embrace new ways of operations in order to sustain their long-term viability and should take on board the same recommendations.

Global supply chains need to be mindful of the variation of service provision amongst CABs, in part manifested by varying levels of digitalisation. Hence, at the firm or supply chain level, firms should engage with ‘digitalised’ and resilient CABs in order to mitigate risks associated with a pandemic or, more broadly, with other disruptions in the supply chains. This observation also translates into particular quality assurance, auditing, and assurance domains. For example, environmental, social, and governance (ESG) reporting also relies on CABs. The use of technologies (remote sensing, satellite imaging, use of cameras, or Artificial Intelligence for data analysis) is increasingly seen as critical for the veracity and timeliness of reporting (Castka et al., 2020b), and only selected CABs are able to deliver such services. Such monitoring includes both environmental aspects (i.e. the use of satellites to monitor biodiversity in food supply chains) as well as social responsibility issues (such as the presence of modern slavery in supply chains and the use of satellites in identifying hotspots).

Conclusions, limitations, and future research

The COVID-19 pandemic has disrupted the global economy, posing major challenges to organisations and highlighting the importance of organisational resilience. Conformity Assessment Bodies (CABs), as central pillars of production, trade, and safety, were also affected by the trickling down of disruptions. This article provides insights into the impact of the pandemic on CABs in Germany and how they responded. It thus sheds light on the resilience of this key sector, allowing us to draw lessons for future crises. While CABs of all fields of activity experienced, on average, varying degrees of order decline at the outset of the pandemic, they proved less dependent on government assistance than companies in other sectors of the economy, and only a few found their business viability at threat. This not only indicates how essential their services are but also the robust resilience of this sector. This study provides an important insight into this domain and paves the way for future studies on the resilience of the conformity assessment (CA) sector as well as resilience more broadly.

Our contribution is fourfold. First, the analysis of the surveyed CABs with the sample description allows for a characterisation of the German accredited CABs in terms of organisational size, international activity, sectors served, and the relation of CABs providing services to internal or external customers. Second, we provide empirical validation on how testing and calibration laboratories and other CABs were impacted by the negative repercussions of the COVID-19 pandemic and how these impacts differed across various CA activities. Third, by conducting multivariate OLS regression analyses, we show how the different CAB-specific characteristics have impacted order development. Fourth, as an implication for theory, we advance the resilience literature by highlighting the important link between contingency plans and flexible response to the pandemic and the subsequent economic effects on organisations.

However, our study is not without limitations, which may offer entry points for future research. First, surveys often suffer from positive bias in response. Second, our findings using multivariate regression analysis do not necessarily imply causality. Third, our analysis was unable to take into account the nature and extent of contingency plans. Hence, future studies could preferably investigate the relationship between contingency plans and response time against the backdrop of flexibility versus stringency of processes during emergencies also relating our finding to Taleb’s (2012) concept of antifragility. Furthermore, future studies could investigate the role of CABs in ‘intertwined supply networks’ (Ivanov & Dolgui, 2020) and the need to safeguard CABs viability. We also proposed possible measures addressed to policymakers and additional actors in the Quality Infrastructure system. To this end, industry networks and research findings could be used to learn from best practices.

Acknowledgments

We would like to thank our colleagues from BAM Federico Cassarà and Timo Kabierski for their support in the preparation and set up of the questionnaire and data evaluation, as well as Petra Keitzl for project management, Dr. Tilman Denkler for valuable input, and Susanne Stobbe for language editing. Finally, the authors gratefully acknowledge the valuable suggestions of two anonymous reviewers.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Data availability statement:

The survey data are publicly available as a report at www.qi-fokus.de

Additional information

Funding

Knut Blind was supported by the Fraunhofer Internal Programs under grant number Anti-Corona 026-600020.Fraunhofer-Gesellschaft